Published first on TheFly – the ultimate source for real-time, market-moving breaking financial news.

Cigna revives merger talks with Humana, Bloomberg reports

Shares of Humana, which has a market capitalization of about $32 billion, were up about 6% in after-hours trading on Friday, while those of Cigna were down about 5%. Cigna was valued at about $94 billion, according to data compiled by LSEG. Cigna and Humana declined to comment.

Cigna resumes mega merger talks with rival health insurer Humana, Bloomberg News reports

Shares of Humana were up about 5% in after-hours trading on Friday, while those of Cigna were down about 2%. Last year, Reuters reported that Cigna ended its attempt to negotiate an acquisition of Humana after the pair failed to agree on a price. Cigna did not immediately respond to a Reuters ...

Cigna resumes merger discussions with Humana, Bloomberg News reports

Executives at Fortune 500 companies from JPMorgan Chase to Cigna Healthcare are reassuring investors that they remain committed to diversity, equity, and inclusion principles, even as mounting attacks on DEI erode certain programs.

Jamie Dimon Among Major CEOs Defying DEI Backlash for Businesses - Bloomberg

GuideWell, a mutual insurance holding company serving more than 38 million people, announced the appointment of Thurman Justice as President and Chief Executive Officer (CEO) of Triple-S Management Corporation,

GuideWell Announces Appointment of Thurman Justice as Triple-S Chief Executive Officer

It’s time to pick health coverage for next year on the Affordable Care Act’s insurance marketplaces, and experts caution against focusing your choice on price alone. In order

It's time to buy health insurance through the marketplace. Experts suggest doing your research first

According to the study “... most expressed flexible time off or work arrangements, followed by a private health insurance plan and mental health support.”

Amid cost of living crisis, SG workers want more health support from employers—study

Exchange insurers are charging more, expanding geographic footprints and creating disease-specific policies to separate themselves from the competition.

Marketplace open enrollment has arrived. Here's what to know

The ACA marketplace’s open enrollment season is also open season for scammers, who look to prey on people overwhelmed by the health insurance marketplace.

No, you won’t get a $6,400 spending allowance from a free health insurance plan

Medicare beneficiaries should watch for shopping surprises when choosing a Medigap plan to avoid paying too much for coverage.

Watch for These 3 Medigap Shopping Surprises to Avoid Overpaying

Cigna

cigna

The response to the murder of UnitedHealthcare CEO, Brian Thompson, last year in Manhattan exposed a torrent of anger by Americans towards the private insurance sector. And the stories of treatment denial shared on social media and legacy media were nothing short of nightmarish: many recounted losing healthcare coverage amid a health crisis, others told of watching their loved one die of a preventable illness as they essayed to secure treatments fighting a megalithic health insurance company that denied them treatment, and there have even been stories from those working within the field of healthcare who related their witnessing the struggles of patients to receive the most basic therapies whilst dying. The problem of treatment denial is so dire that even American cancer organizations have had to devote part of their mandate to assisting patients in obtaining healthcare coverage from their insurers. 1.7 million Americans a year die of chronic disease. Americans pay more for healthcare than any other wealthy nation in the world yet Americans receive poorer care. According to the Peterson Foundation, US healthcare spending per capita is almost twice the average of other affluent countries. In 2022, U.S. healthcare spending reached $4.5 trillion, averaging $13,493 per person. With the rise of Health Maintenance Organisations (HMOs) in the 1980s, healthcare in the US has shifted towards a model that cynically puts profits before health such that these HMOs were able to score a profit from the delaying of medical treatments, thus prolonging of chronic disease. The PBM (pharmacy benefit manager) structure was established in the 1970s as a tool to protect citizens from pharmaceutical inflation, with a mandate to drive down the costs of prescription drugs. However, as insurance companies grew in size and scope across the country, they started to purchase these PBMs which quickly became the profit-making centres of insurance companies. From the 1980s onward, the mandate of PBMs shifted radically from of keeping the costs of prescription medicine down to driving these costs upwards. By increasing the price of prescription drugs the pharmaceutical companies pay the PBMs (approximately one-third of pharmaceutical costs), and pharmaceutical companies are ensured placement on a preferred contract with insurance companies whilst the PBM reaps huge economic benefits. In short, insurance conglomerates have profiteered from chronic disease from both sides of the "equation"—from insurance premiums and their stake in profits made through the sales of pharmaceutical products to the individual. And the profits made by Big Pharma are not negligible. UnitedHealthcare, for instance, generated $371.6 billion in revenue in 2023. What is important here is that 60% of its revenue came from its PBM, a holding company that is obfuscated by the public and government. The profit margins of insurance companies, while not as high as Big Pharma, these companies are able to hide their profitability much of which is held at the PBM while artificially representing a small profit than in reality. In 2023, sixteen of the largest drug companies in the United States reported $684 billion in earnings. According to GreedWatch, this figure is “higher than the gross domestic product (GDP) of 88 percent of the countries in the world.” And since the ACA (Affordable Care Act) passed in 2010, America’s largest health insurers have raked in more than $371 billion in profit. And of this profit, more than 40 percent went to UnitedHealth Group, a company whose annual profits have skyrocketed by nearly 400 percent as the company is on record denying nearly one in three medical claims from its policyholders. UnitedHealthcare is one of many insurers that have set up shop for the purpose of capturing new clients due to Obama’s ACA which guaranteed this industry more—not less—business. In addition to the more traditional health insurance models, there is now the growth of new sectors from Embedded Insurance 2.0  (EI 2.0) to the company registration of various tertiary markets that feed the insurance market (eg. adaptable technologies, Health 2.0 technologies, and AI). Profitability within this sector is soaring. And this is the crucial bit that many in Britain have failed to understand given how legacy media pushed the ACA (formerly known as Obamacare) as some sort of “golden goose” for socialized medicine in the United States: the ACA mandated Americans to buy insurance while providing government subsidies for such insurance policies. The ACA effectively forced poor Americans to purchase private health insurance where many politicians were clamoring for a far more socialist response: to change the eligibility for Medicaid (a joint federal and state program that helps cover medical costs for some people with limited income and resources). Since the ACA was passed, more than $9 trillion of revenue has been discharged to the country’s largest health insurance companies which include UnitedHealth Group, Cigna; Kaiser Permanente, Elevance Health, the parent company of Anthem Blue Cross Blue Shield, and CVS Health, which acquired Aetna in 2018. From 2014 when the ACA was in vigour, the revenue and profits substantially increased. Recent Gallup polling data shows how Americans’ rating of health care quality has declined to a 24-year low. Add to this the rising rates of bankruptcy due to medical debt resulting in roughly 530 000 medical bankruptcies annually or how approximately one million Americans go to Mexico for healthcare while being unable to afford it back home. As the facts roll in regarding Americans' extortionate medical system and the industries scoring a profit from keeping people chronically ill, the acrimonious response to the insurance industry triggered by Thompson’s murder in December becomes far more understandable. More than two-thirds of all deaths in the United States are caused by one or more of these five chronic diseases: heart disease, cancer, stroke, chronic obstructive pulmonary disease, and diabetes. According to the NIH (National Institutes of Health), chronic disease is killing more than 1.7 million Americans a year, more than the casualty of all wars the US has ever fought. While the NHS has its struggles and private insurance is on the rise within Britain largely due to NHS queues, the situation in the United States serves as a warning of the dangers of private healthcare. What the Trump administration says it will do and what it will actually do regarding this pandemic of ill-health among the populace and the private insurance industry remains to be seen. But one thing is certain: Americans are more sick than they are tired of the situation. The response to the murder of UnitedHealthcare CEO, Brian Thompson , last year in Manhattan exposed a torrent of anger by Americans towards the private insurance sector. And the stories of treatment denial shared on social media and legacy media were nothing short of nightmarish: many recounted losing healthcare coverage amid a health crisis, others told of watching their loved one die of a preventable illness as they essayed to secure treatments fighting a megalithic health insurance company that denied them treatment, and there have even been stories from those working within the field of healthcare who related their witnessing the struggles of patients to receive the most basic therapies whilst dying. Brian Thompson Brian Thompson The problem of treatment denial is so dire that even American cancer organizations have had to devote part of their mandate to assisting patients in obtaining healthcare coverage from their insurers. The problem of treatment denial is so dire that even American cancer organizations have had to devote part of their mandate to assisting patients in obtaining healthcare coverage from their insurers. assisting patients assisting patients 1.7 million Americans a year die of chronic disease. Americans pay more for healthcare than any other wealthy nation in the world yet Americans receive poorer care. According to the Peterson Foundation , US healthcare spending per capita is almost twice the average of other affluent countries. In 2022, U.S. healthcare spending reached $4.5 trillion , averaging $13,493 per person. With the rise of Health Maintenance Organisations (HMOs) in the 1980s, healthcare in the US has shifted towards a model that cynically puts profits before health such that these HMOs were able to score a profit from the delaying of medical treatments, thus prolonging of chronic disease. Peterson Foundation Peterson Foundation $4.5 trillion $4.5 trillion The PBM (pharmacy benefit manager) structure was established in the 1970s as a tool to protect citizens from pharmaceutical inflation, with a mandate to drive down the costs of prescription drugs. However, as insurance companies grew in size and scope across the country, they started to purchase these PBMs which quickly became the profit-making centres of insurance companies. From the 1980s onward, the mandate of PBMs shifted radically from of keeping the costs of prescription medicine down to driving these costs upwards. By increasing the price of prescription drugs the pharmaceutical companies pay the PBMs (approximately one-third of pharmaceutical costs), and pharmaceutical companies are ensured placement on a preferred contract with insurance companies whilst the PBM reaps huge economic benefits. In short, insurance conglomerates have profiteered from chronic disease from both sides of the "equation"—from insurance premiums and their stake in profits made through the sales of pharmaceutical products to the individual. And the profits made by Big Pharma are not negligible. Big Pharma Big Pharma UnitedHealthcare, for instance, generated $371.6 billion in revenue in 2023. What is important here is that 60% of its revenue came from its PBM, a holding company that is obfuscated by the public and government. The profit margins of insurance companies, while not as high as Big Pharma, these companies are able to hide their profitability much of which is held at the PBM while artificially representing a small profit than in reality. $371.6 billion in revenue $371.6 billion in revenue In 2023, sixteen of the largest drug companies in the United States reported $684 billion in earnings. According to GreedWatch , this figure is “higher than the gross domestic product (GDP) of 88 percent of the countries in the world.” And since the ACA (Affordable Care Act) passed in 2010, America’s largest health insurers have raked in more than $371 billion in profit. And of this profit, more than 40 percent went to UnitedHealth Group, a company whose annual profits have skyrocketed by nearly 400 percent as the company is on record denying nearly one in three medical claims from its policyholders. GreedWatch GreedWatch “higher than the gross domestic product (GDP) of 88 percent of the countries in the world.” UnitedHealthcare is one of many insurers that have set up shop for the purpose of capturing new clients due to Obama’s ACA which guaranteed this industry more—not less—business. In addition to the more traditional health insurance models, there is now the growth of new sectors from Embedded Insurance 2.0 (EI 2.0) to the company registration of various tertiary markets that feed the insurance market (eg. adaptable technologies, Health 2.0 technologies, and AI). Profitability within this sector is soaring. Embedded Insurance 2.0 Embedded Insurance 2.0 company registration company registration And this is the crucial bit that many in Britain have failed to understand given how legacy media pushed the ACA (formerly known as Obamacare) as some sort of “golden goose” for socialized medicine in the United States: the ACA mandated Americans to buy insurance while providing government subsidies for such insurance policies. The ACA effectively forced poor Americans to purchase private health insurance where many politicians were clamoring for a far more socialist response: to change the eligibility for Medicaid (a joint federal and state program that helps cover medical costs for some people with limited income and resources). eligibility for Medicaid eligibility for Medicaid Since the ACA was passed, more than $9 trillion of revenue has been discharged to the country’s largest health insurance companies which include UnitedHealth Group, Cigna; Kaiser Permanente, Elevance Health, the parent company of Anthem Blue Cross Blue Shield, and CVS Health, which acquired Aetna in 2018. From 2014 when the ACA was in vigour, the revenue and profits substantially increased. Recent Gallup polling data shows how Americans’ rating of health care quality has declined to a 24-year low. Add to this the rising rates of bankruptcy due to medical debt resulting in roughly 530 000 medical bankruptcies annually or how approximately one million Americans go to Mexico for healthcare while being unable to afford it back home. As the facts roll in regarding Americans' extortionate medical system and the industries scoring a profit from keeping people chronically ill, the acrimonious response to the insurance industry triggered by Thompson’s murder in December becomes far more understandable. Gallup polling Gallup polling medical debt medical debt Mexico Mexico More than two-thirds of all deaths in the United States are caused by one or more of these five chronic diseases: heart disease, cancer, stroke, chronic obstructive pulmonary disease, and diabetes. According to the NIH (National Institutes of Health), chronic disease is killing more than 1.7 million Americans a year, more than the casualty of all wars the US has ever fought. 1.7 million Americans 1.7 million Americans all wars all wars While the NHS has its struggles and private insurance is on the rise within Britain largely due to NHS queues , the situation in the United States serves as a warning of the dangers of private healthcare. What the Trump administration says it will do and what it will actually do regarding this pandemic of ill-health among the populace and the private insurance industry remains to be seen. But one thing is certain: Americans are more sick than they are tired of the situation. on the rise on the rise NHS queues NHS queues

The Monetisation of Illness

Monetizace nemoci

La monetización de la enfermedad

Gaixotasunaren dirua irabaztea

बीमारी के मुद्रास्फीति

Monetize maladi

病気の金銭化

Монетизација на болеста

Monetarisatie van de ziekte

Gukoresha Indwara

Monetariseringen av sjukdomen

การหารายได้จากความเจ็บป่วย

Ku Endliwa ka Mali ya Mavabyi

Inside the Degen Mind: Understanding Crypto Communities and Why We Are the Way We Are

በዴጄን አእምሮ ውስጥ-የ Crypto ማህበረሰቦችን መረዳት እና ለምን እነሱ እንደነበሩ መረዳት

Unutar uma Degena: Razumijevanje kripto zajednica i zašto su takve kakve jesu

Dentro de la mente de Degen: comprensión de las comunidades criptográficas y por qué son como son

डेगन माइंड के अंदर: क्रिप्टो समुदायों को समझना और वे जिस तरह से हैं, क्यों हैं

Inside the Degen Mind: הבנת קהילות קריפטו ומדוע הן כפי שהן

Degen の心の中: 暗号通貨コミュニティを理解し、なぜそれが今のような形になっているのか

Na kati ya makanisi ya Degen: Kososola ba Communautés Crypto mpe Pourquoi Bazali Ndenge Bazali

Дегений оюун санааны дотор: Крипто нийгэмлэгүүд ба тэд яагаад ийм байдгийг ойлгох

डिजेन माइन्ड भित्र: क्रिप्टो समुदायहरू बुझ्दै र तिनीहरू किन छन् जसरी तिनीहरू छन्

Wewnątrz umysłu Degena: zrozumienie społeczności kryptograficznych i dlaczego są takie, jakie są

Degen aklynyň içinde: Kripto jemgyýetlerine we näme üçin olaryň beýle bolandygyna düşünmek

Bên trong tâm trí Degen: Hiểu về cộng đồng tiền điện tử và lý do tại sao họ lại như vậy

Thanks to big data, today an organization can quickly obtain the necessary information from an unordered data set and deploy it effectively. The growing popularity of big data analytics has led to a significant increase in the number of companies providing big data solutions and related services. Today, there are in the global market, and this number may be very confusing. Big data skills, experience, and related technical expertise can significantly vary among vendors, which may puzzle anyone looking for a big data service provider. almost 1000 big data analytics companies How to identify the best big data consulting firms I set myself the goal to identify the most reliable big data consulting companies on today’s IT market. To do this, I investigated hundreds of data providers and studied their characteristics. Each company was analyzed according to the set of specifically designed criteria. Among the criteria are big data expertise, major clients, offering strategy, track record, and online reviews. Below you can see the results of the conducted market research. 1. Itransition Founded in 1998, Itransition is a custom software development company that provides big data consulting and platform engineering services. The company also offers business intelligence (BI) portals development and boosts them with machine learning (ML) and other technologies. The company offers data store design, data migration, performance optimization, and support services. The company’s client base includes IBM, Expedia, Toyota, eBay, Xerox, PayPal, and Adidas. With more than 150 completed projects and 810 clients worldwide, IAOP recognizes the company as one of The Global Outsourcing 100. Denver, CO Headquarters: Expedia, Xerox, Toyota, eBay, IBM, PayPal, Adidas Core clients: $25 — $49 Pay per hour: 1000–9999 Number of employees: Website: https://www.itransition.com/ 2. Saviant Consulting Saviant is a consulting company with more than 120 experts in its team and more than 100 clients in various countries, including UK, Canada, and the US. The company specifically focuses on Energy, Logistics, and Retail. Among the company’s big data services are big data analytics and management, full-cycle big data solution development, and more. Pune, India Headquarters: JJ Food Service, BuilderMT, Transparent Technologies, Inc Core clients: Not Revealed Pay per hour: 50–249 Number of employees: Website: https://www.saviantconsulting.com/ 3. Squadex Headquartered in California, USA, Squadex is a technology consulting and engineering company that provides big data services. It offers big data analytics, consulting, and big data platform engineering. Squadex is an AWS certified consulting partner that works with companies of different size, from small startups to large enterprises. Palo Alto, CA Headquarters: Model N, NinthDecimal, Nitrio Core clients: Not Revealed Pay per hour: 250–999 Number of employees: Website: https://squadex.com/ 4. CBIG Consulting Founded in 2002, CBIG Consulting is an American company offering business intelligence and big data analytics solutions. Besides analytics and consulting, the company provides big data solutions architecture. For this purpose, CBIG Consulting employs Hadoop distributions, Hive, Sqoop, etc. The company’s industrial focus is on Finance, Healthcare, and Retail. Chicago, IL Headquarters: Abbott, Astellas, Baxter, Cigna, DePaul University Core clients: $150 — $199 Pay per hour: 50–249 Number of employees: Website: https://www.cbigconsulting.com/ 5. Clavax Technologies Founded in 2011, Clavax is a software development company headquartered in San Jose, California. It delivers big data consulting and implementation. By employing big data technologies, the company provides services for data warehousing, data processing, and data integration. Clavax’ client list includes PWC, Football.com, Bookfari, and Honeywell. San Jose, CA Headquarters: PWC, Football.com, Bookfari, Honeywell, Jabil Core clients: $25 — $49 Pay per hour: 50–249 Number of employees: Website: https://www.clavax.com/ 6. ThirdEye Data ThirdEye Data is a big data services company that delivers big data consulting, analytics and engineering while using artificial intelligence, deep learning, and machine learning. ThirdEye Data has served such companies as Nokia, Ford, Amgen, GettyImages, Actian, and others. The company focuses on Finance, Government, IT, Retail, and Manufacturing. Santa Clara, CA Headquarters: Microsoft, Nokia, Ford, Amgen, GettyImages, Actian, Google Core clients: $50 — $99 Pay per hour: 50–249 Number of employees: Website: https://thirdeyedata.io/ 7. Signity Solutions Established in 2009, Signity Solutions is a company that delivers custom software development and big data solutions. The company helps with big data analysis and brings data solutions empowered by machine learning. Signity works for the Commerce, Education, Media, and other industries. Rajiv Gandhi IT Park, India Headquarters: Samsung, Grupio, The Project Factory Core clients: $25 — $49 Pay per hour: 50–249 Number of employees: Website: https://www.signitysolutions.com 8. Caserta Founded in 2001, Caserta is a NY-based IT company that delivers a wide range of data-related services. The company offers big data consulting and solution architecture/development. Caserta also provides data visualization, data warehousing services, and more. The company has worked with such clients as New York Times, Capital One, Equinox, and HBO. New York, NY Headquarters: New York Times, Capital One, Equinox, HBO Core clients: Not Revealed Pay per hour: 10–49 Number of employees: Website: https://caserta.com/ 9. RapidOps, Inc RapidOps is a custom software development company based in the USA. The company’s expertise includes big data analytics, consulting, and visualization. The company’s team of 60+ professional developers delivers its services to the Manufacturing, Retail, and IT industries. Charlotte, NC Headquarters: YoDish, Zurn Industries, DassaultSystemes Core clients: $25 — $49 Pay per hour: 50–249 Number of employees: Website: https://www.rapidops.com/ 10. Aegis Soft Tech Since 2003, Aegis Soft Tech has been providing software development to Healthcare, Finance, Retail, Manufacturing, and other industries. Aegis provides big data consultation, management, and analysis. Among that, Aegis helps with data migration processes. The company’s pool of developers expertizes in Hadoop, Cloudera, and Hortonworks platforms. Rajkot, India Headquarters: Sunzinet, Zydus, PointRF, Efacec Core clients: < $25 Pay per hour: 50–249 Number of employees: Website: https://www.aegissofttech.com/ 11. GetInData GetInData is a Poland-based company that unites more than 30 professionals. The company has carried out more than 30 projects. GetInData delivers the following big data services: big data infrastructure development, analytics, consulting, engineering, and maintenance. GetInData delivered its services to such companies as Spotify, Allegro, Agora, and Freshmail. Warsaw, Poland Headquarters: Spotify, Allegro, Agora, Freshmail, Truecaller, GoEuro Core clients: $50 — $99 Pay per hour: 10–49 Number of employees: Website: https://getindata.com/ 12. Kavi Global Established in 2008, Kavi Global is an analytical company that delivers a whole spectrum of big data services. They include consulting, big data solution architecture, and platform implementation. The company also offers data mining and data management services. Kavi Global’s industrial expertise includes Transportation, Manufacturing, Education, and Healthcare. Barrington, IL Headquarters: General Electric, TEAMHealth, Thomson Reuters, Ryder Core clients: $150 — $199 Pay per hour: 10–49 Number of employees: Website: https://www.kaviglobal.com/ 13. Indium Software Since 1999, Indium Software has been providing technological solutions for 19 various industries. The company has worked with 750 clients from all over the world. Employing such technologies as Hadoop, Spark, and Apache Kafka, Indium Software delivers big data architecture and consulting services. Princeton, NJ Headquarters: Not Revealed Core clients: < $25 Pay per hour: 250–999 Number of employees: Website: https://www.indiumsoftware.com/ 14. Fayrix Israel-based Fayrix is a custom software development company and big data services provider with 1530 IT experts on board. The company deals with various projects, from initial data analysis and consulting to big data infrastructure design, big data software development, and its implementation into a client’s existing technological landscape. Pitu’akh, Israel Headquarters: Biosence Webster, SCR, S7 Airlines Core clients: < $25 Pay per hour: 1000–9999 Number of employees: Website: https://fayrix.com/ 15. Denologix Established in 2002, Denologix is an analytics and information management company providing a wide range of big data services, including data analysis, consulting, and big data solution implementation and support. The company deploys a large number of technological tools for big data, including Hortonworks Data Platform, Cloudera СВР Hadoop Distribution, and more. Among the company’s clients are Adidas, Allstream, Aviva, Canada Post, and others. Toronto, Canada Headquarters: Adidas, Allstream, Aviva, Canada Post, Bell, Brookfield Core clients: $150 — $199 Pay per hour: 50–249 Number of employees: Website: http://www.denologix.com/ 16. Data Reply Established in 2015, Data Reply is a big data and analytics consultancy based in London, UK. Besides big data consulting and training, the company offers data engineering and data science services. The company focuses on such industries as Retail, Media, Telecommunications, and Commerce. London, United Kingdom Headquarters: Not revealed Core clients: $100 — $149 Pay per hour: 10–49 Number of employees: Website: https://www.datareply.co.uk/ 17. Dexlock Established in 2012, Dexlock is an Indian company that delivers big data services. Among them are large data store development and deep learning/machine learning implementation. The company’s technological expertise includes Hadoop, Apache Spark, Apache Kafka, and more. Dexlock works with the Healthcare, Retail, Insurance, Energy and other industries. Kochi, India Headquarters: FindCharisma, Splash of Colors, StatFuel, MyPeepz Core clients: < $25 Pay per hour: 50–249 Number of employees: Website: http://www.dexlock.com/ 18. 47Billion 47Billion is a bespoke software development company that provides mobile and web development and UI/UX design. Besides these services, the company delivers end-to-end big data analysis, consulting, and engineering. The company’s industrial focus includes IT, Gaming, and Consumer Services. 47Billion’s clients include Cisco, Nazara, and Apsalar. Bangalore, India Headquarters: Cisco, Nazara, Apsalar Core clients: : $25 — $49 Pay per hour 50–249 Number of employees: Website: https://47billion.com/ 19. 51zero 51zero is a UK-based company that specializes in big data services providing. The company delivers big data consulting and solutions development and focuses on the financial service domain. The company’s pool of technological experts deploys such big data technologies as Spark, Apache Kafka, Docker, and others. London, United Kingdom Headquarters: HSBC, The Royal Bank of Scotland, Barclays Core clients: $200 — $300 Pay per hour: 2–9 Number of employees: Website: https://www.51zero.com/ 20. SCI-BI SCI-BI is a company based in India. With more than seven years of experience, the company specializes in big data consulting and engineering. The company also helps with data integration strategy. SCI-BI’s big data technological expertise includes Cloudera and Hortonworks. The company focuses explicitly on Logistics and Retail. Chennai, India Headquarters: Executive Planning Services, USA SaasByDesign Inc, USA Caravel Logistics Core clients: < $25 Pay per hour: 10–49 Number of employees: Website: http://sci-bi.com/

The Top Big Data Consulting Firms

Healthcare Innovation in 2018

245 Tools & Resources for Travelers and Digital Nomads

What is Brand Management Software? Brand Management tools are helpful to businesses in order to manage their brand globally and locally and you can easily ensure yourself that your branding is in your control. Brand owners or managers can easily manage the complete brand messaging of their business with the help of brand management software. A business owner or brand manager can easily create an effective discipline for those who represent their brand; agencies, vendor partners and other marketing sources represent the brand in the market so the brand manager can easily create the effective roadmap for them and it really increases the brand reputation in the market. The user can easily get a centralized database where he/she can create, manage, store, share and distribute the brand assets and relevant files. This thing really increases brand consistency in all different stages. If you need to create new marketing techniques and strategies for your brand and you need the best process to regulate it, brand management software is the best solution for you where you can easily manage workflow process. You can also approve new marketing techniques and other activities to boost your brand power and awareness. Let’s take a look, here you can find the leading brand management software for your business. 1. Brand24 Discover what people are saying online about your brand — as it unfolds in real time. Brand24 gives you instant access to mentions about your brand across the web, from social networks to influential publishers. React and engage quickly to real-time comments made about your brand. Follow-up on positive comments from your brand ambassadors, or respond to a dissatisfied customer before the story gets ahead of you. 2. Widen Collective Widen Collective is a cloud-based digital asset management solution that allows users to find, share, upload, download and analyze visual content anywhere, on any device. The product is suitable for marketers, creative teams, IT managers and software architects of SMBs and enterprises. It is designed to cater to the needs of various industries that include apparel, construction, consumer goods, hospitality, healthcare, engineering, medical devices, travel and retail. 3. Grade.us If you’ve got your pulse on growing tends in digital marketing, you know the importance of online reviews. Not only are they an increasingly valuable ranking factor for search engines, they are becoming an inevitable step for your customers as they look to make a purchase decision themselves! In other words, they help you get more customers because of visibility and influence. 4. Justuno Justuno is the most innovative and robust conversion optimization suite for sales conversions, email list growth, and onsite promotions using real-time user data. We deliver powerful results for agencies, grow audiences for brands, and increase conversions for merchants. 5. Cision Cision covers all aspects of your communication needs, helping you reach, target and engage your audience. The Cision Communications Cloud® features a suite of metrics and automated analyses that translate your activities and earned media coverage into valuable insights and most importantly verifiable return-on-investment. 6. Reputology Reputology is the review monitoring and management solution designed for organizations that operate multiple physical locations. We help restaurants, gyms, hotels, auto dealers, hospitals, marketing agencies, retail stores, banks & more. 7. Percolate Percolate offers solutions to introduce visibility into the marketing process, improve coordination of work, and effectively build marketing campaigns and content. The world’s largest brands — including Mastercard, Cisco, Cigna, Electronic Arts, and Bosch — use Percolate to create a coordinated customer experience, reduce production costs, and understand marketing impact. 8. Bynder Bynder’s success is not only down to the quality of our work and outstanding customer care, but it’s driven by the attitude and approach of our global team. We believe focused and passionate teamwork should influence everything we do, and our desire to produce exceptional solutions runs deep. We are united with you in the drive to get the best from your project; we listen hard to understand your business and your needs, and we’re 100% committed to making all our features the best they can possibly be. 9. Prisync Prisync is a competitor price tracking & dynamic pricing software for all sizes of e-commerce companies from all around the world. It tracks online prices and stock availabilities and lets e-commerce companies define smart pricing rules depending on their unit product costs and competitor prices to apply dynamic pricing on their webshop to increase sales and profit margins. Prisync is already helping various sizes of e-commerce companies from more than 40 countries. 10. Asset Bank The first version of Asset Bank was established in 2005. We were inspired to enter the world of Digital Asset Management (DAM) after developing a bespoke image management system for our client GKN Driveline. As part of the development process we realised there were quite a few companies already offering DAM systems, but at an exorbitant cost. Our vision was to offer quality DAM software at a great price. 11. Frontify Frontify is the SaaS-based brand management platform for the digital age used by 2000 companies worldwide including Vodafone, Lufthansa, IBM, Nasdaq, and Bosch. With our cloud-based software, brand managers can create online Style Guides, manage their brand assets, create UI Pattern Libraries, Brand Portals and work collaboratively in creative projects. Strengthen your brand consistency over all channels using Frontify. Ideally suited for Enterprise level companies. 12. NiceJob NiceJob is a reputation marketing solution to aid businesses with gathering more and better quality reviews, marketing across social platforms, and improving SEO ranking. With the aim of helping businesses of any type or size to improve their online reputation, NiceJob provides tools such as review invitations, automated email and SMS follow-ups, review funnels, stories, SEO management, and more. 13. Third Light Third Light is a fast, feature-rich, digital asset management tool. Organise, tag, find, share, edit and download all of your digital files quickly, easily and securely. Online chat and share supports centralized, collaborative working with internal teams and external partners. Convert formats, trace copyright, protect and distribute files. Cloud-based or licensed solutions with free, seamless updates and API available. Great price, offers unlimited users and supports industry standards. 14. Outbrain Outbrain is a premium discovery platform that helps connect marketers to their target audience through personalized recommendations on the world’s leading publishers. We use proprietary interest and behavioral data to capture audience’s attention all the way to inspiring their next action. 15. CleanPix CleanPix is a web-based digital, brand, and media asset management solution which automatically processes files into multiple sizes and formats, enables users to organize assets into public and private galleries, and allows distribution of assets through public portals, access-controlled private galleries, and directly by email. The Core Elements of Brand Management Software Brand Management software is specially designed for all sizes business where a brand manager can easily organize and advertise their products and services to their most potential customers in the most effective manner. We can also understand this software as marketing category software. Here you can find the most essential elements of brand asset management software: Effective Marketing Campaigns: As I told you earlier that it manages to brand globally and locally however it also works to maintain brand loyalty internally and externally. Marketing is one and the only option to reach your audience so you can easily reach to your audience and create the effective brand awareness with the help of brand management tools. You can create a robust and error-less marketing campaign with these branding tools. Project Workflows: You can easily manage project workflows with brand management software; it usually takes care of your all work steps; you can also track the workflow with the same software. You can create new marketing strategies and regulate it to across all channels. You can create the effective work cycle at all channels of business and it will help you to create the best workflows. You can easily increase the team collaboration level with brand management. Design Assets: Design defines the business. It attracts the customer and increases brand value so never compromise with design assets. You can easily develop and market impactful designs which one shows the higher relevancy of your business. You can create designs in any format and share directly to social media with the help of brand management tools. You can even restore the asset and recreate the design with your team. Social Media Social media is the most powerful way for you if you really want to reach to your audience. You can easily create relevant and impressive designs with this type of tool and directly share to social media. You can easily integrate any of social media platforms into your brand management software. You can easily double your social media effort through brand management software. Common Functionality of Brand Management: Here, I am going to show you some most common functionality of brand management software. Social Media Integration: You can easily integrate your brand management software with your business social media handles like Facebook, Twitter, Google+, Linkedin, Tumblr, Reddit and much more. It really creates the easiest way to do social media for your business. Real-time analytics You can easily access real-time analytics across the complete brand management process. You can easily get an idea about critical insights through this software. User-defined permissions You can easily provide and denied access to the particular user. You can deliver and share your business assets to the right person with this feature. Search functionality It’s the best option to locate the right asset in right time. You can search and get needed assets anytime with this feature. Multi-format output You can easily create your content in multi-format like you can create content in PDF, HTML, and other formats. Fulfillment distribution You can easily distribute the relevant asset to the right users and groups in seconds even you can control your distribution among users. Asset management The User can easily create, store and manage all the marketing and design assets even he/she can share with others within certainly located online portal or database. Artwork automation It allows the user to streamline design processes and this thing really improves the brand accuracy and productivity level of the particular user. Approval Process Control The user can easily review the social media posts and marketing strategies and after they can manually or automatically approve it. Alert Feature The user can easily send alerts to a particular user or group regarding content reviews and approval stages. It will also help to generate custom email alerts to the selected groups. What things buyers should keep in mind? As I told you that it works for all size businesses as per their needs so before choosing the best software, you must have to understand your needs. If you are the small business owner, cloud-based brand management software is the best option for you because of its affordable and cost-effective options to manage your branding. 1. For larger and big enterprises, there is another category of corporate brand management software where you can find the on-premise solution for your brand. You can easily organize and control in-house branding activities with the help of this software. 2. You must also understand the third-party integration features of software because of it will make your way easier with proper integration. You can integrate your social media accounts, email accounts, online store, your website and much more thing to your brand management software. 3. Why You Need Brand Management Software For Your Business? You can do many things manually to increase your business but it only offers limited space. All the successful company works on big data and analytics and if you want to work with big data, brand management tools are the best option to make your system automated. You can easily discover more useful insights and understand your customer needs very well. You can even enter to the new market with the help of valuable and exact data. Mobile offers major traffic to brands than desktop, laptop, and other devices. Most returning users and new users (approx 51%) interact with mobile to the brand so the business turns their approach to mobile devices. You can easily integrate your brand software to your mobile app and create effective marketing and branding strategies for your business.

List of Top 10+ Brand Management Software With Ultimate Buyer Guide

Originally published on Scrappy & Strange, the Founder Collective Newsletter — Sign up here ! David Frankel relayed this quote from , which was delivered at annual gathering, as a reminder that capital is a constraint — though probably not the biggest constraint facing most startups. Hustle tends to be in much shorter supply. Here are a few inspiring stories of entrepreneurs illustrating the power of hustle over capital: Regie Gibson Cue Ball Capital’s Instead of investing in costly ad campaigns in the company’s cash-strapped early days, , with ultra-specific names like “RacksAndStands.com” to game Google’s search algorithm, paving the way for what has become a $4B business. Wayfair: Wayfair built 270 highly targeted websites a $2B stock photo service, was started by a hacker/amateur photographer who personally built the site and launched it with 100,000 images from his photo collection. ShutterStock , Hustle doesn’t stop once you have raised venture capital. Langley Steinert raised $5M to get CarGurus started, but instead of seeking VC to hire even more engineers, he used the revenue he was generating to hire — now the company is cruising towards an IPO. CarGurus: hundreds of sales reps to generate even more revenue Meet The Efficient Entrepreneur Who Replaced RadioShack Limor Fried, founder/CEO of AdaFruit. Photo: . Make: Magazine started out of her dorm room at MIT and has bootstrapped her ecommerce/electronics startup (now based in NYC) to $45M in revenue with 105 FTEs, and a product line which features 400+ hardware products and kits. Read this profile to learn more about the company, including how they’ve acquired 20M+ YouTube views, 100K Twitter followers, and 2M monthly website visits. Limor Fried AdaFruit Make: Magazine Unity Raised No VC for its First Four Years, Gets $400M in One Round , makers of the game engine that powers Pokemon Go and just raised . Even more interesting is the of how the founders hustled during the company’s first four years, building out , before raising . Unity 34% of top mobile games $400M from PE giant Silver Lake history mobile-friendly 3-D rendering tech forgoing salary, and even waiting tables to pay the bills venture capital Should Startups Care About Profitability? makes a compelling argument that profitability is overrated for companies that are well suited to venture capital. It’s a nuanced argument, but one that almost any entrepreneur would benefit from reading. Here’s an excerpt: Mark Suster If the market they are targeting is very large and fast growing, then the venture-backed businesses often make it harder for the non-venture-backed businesses to compete in the long-term. If the markets aren’t large then the company who managed its costs may be able to get a modest exit at a fair price and make the team wealthy precisely because they didn’t take on venture capital. The VC-backed businesses sometimes “blow up.” As is often the case — there are no obvious or right answers. responded with a post about the beneficial effects enjoyed by his portfolio companies that have prioritized profitability. shared his experience from the dot-com era, “I learned that the markets reward growth until they don’t. Then they reward profitability.” Also, be sure to read to the discussion. Fred Wilson Brad Feld Roger Ehrenberg’s thoughtful contribution Weirdness from Around the Web Filmmaker replaces missing eyeball with a video camera. [ ] Motherboard “During a recent type-in at Albuquerque soul food restaurant Nexus Brewery, around three dozen fans took turns clicking the keys of an Italian-made 1964 Olivetti Lettera 32 Typewriter.” [ ] MySanAntonio British researchers scan 6,000 faces to create database for plastic surgeons to use for reconstructive surgery [ ] 3Ders The first blue pigment created in over 200 years to be used in a crayon [ ] Colossal Founder Collective in the News Deconstructing the “Near” Perfect Deal — Our Investment in Julia Computing By D avid Frankel , Partner An excerpt: I’m fortunate to have been involved with some amazing entrepreneurs and startups over the years, but each of those deals had some flaw when I invested. These obviously weren’t disqualifying; it’s just the reality that high-risk seed-stage venture investing is predicated on … risk. That’s why I’m both excited and somewhat concerned that I’ve recently had the opportunity to invest in a deal that is as close to the platonic ideal that I’m ever likely to see. Want to know what makes a deal “near” perfect? Read More! What Startups & VCs Can Learn From Indiana Jones By Micah Rosenbloom , Partner An excerpt: It might be a useful exercise for founders to think of themselves as auteurs rather than entrepreneurs. Filmmakers and founders are both creative professionals, but directors have to contend with a world where capital is a fixed sum, not a seemingly endless stream. Directors must have a vision for their product, a rough understanding of what it would cost to realize that vision, and then execute within those constraints. Contrast that to startup founders who always have the possibility of raising another round of funding. Strict limitations for filmmakers have led to a slew of indie projects, made on shoe-string budgets by unknown creators, that go on to rival star-studded Hollywood blockbusters. For instance: These are career-making projects that put stars, and catchphrases, on the map. All were made — at most — with a series A level of funding. What makes these low-budget films so successful? There seem to be a few common themes: Want to know what Napoleon Dynamite can teach your startup? . Read the rest here There’s No Shame in a $100M Startup By E ric Paley , Partner & Joe Flaherty , C&C We’ve expanded our list of and found that billion dollar outcomes remain in short supply. entrepreneurs who have become VCs Portfolio Updates CEO Zach Bookman appeared on CNBC to discuss how tech companies can help streamline and strengthen government services OpenGov [CNBC] raised $50M from Cigna to fight diabetes Omada Health [Omada] announced a new package design and PharmacyOS PillPack [Wired] released data demonstrating that meal delivery apps don’t cannibalize restaurant sales. S ense360 [CNBC] breaks down the new changes to Apple’s podcast ecosystem Bumpers [Bumpers] is one of the Wall Street Journal’s “25 Tech Companies to Watch” Andela [WSJ] Job of the Week 3-D Printing market leader is looking to hire 100+ people in the next year, but first, they need to find an . Do you know how to seek out the best software engineers? The techniques to attract top notch talent in engineering, design, marketing, and sales? If so, Formlabs is building something amazing — be a part of it. Formlabs ace recruiter

“Hustling is the art of practicing capitalism without capital”

Speaking at CES on 6 January 2025, Jensen Huang, CEO of NVIDIA, delivered the keynote address from the digitally recreated NVIDIA headquarters, painting a fascinating picture of how artificial intelligence is making impact across industries and everyday life. AI in Your Pocket: Introducing NVIDIA Project DIGITS One of the most intriguing announcements was NVIDIA's Project DIGITS, a new AI-powered personal supercomputer. Huang was impressed by its compact design, similar to the 'size of a pack of cigarettes', but capable of delivering a petaflop of computing power. This innovation aims to democratize AI supercomputing by making it accessible to small labs, lone professionals, and even home users (NVIDIA Project Digits). Consider a scenario where researchers have access to significant computational resources directly from their workstations. This eliminates dependencies on cloud computing or traditional supercomputers, which can be limited by availability and cost. In this setting, a scientist working in a smaller lab could conduct their research with greater autonomy, utilizing a powerful, localized supercomputer. This accessibility to high-performance computing would enable individual scientists and smaller teams within startups to engage in AI research more readily. This shift could lead to increased research and development activities, as barriers to computational resources are reduced. Data analysis and model training could be performed more quickly and iteratively. Consequently, this future could see more individuals and organizations participating in scientific and technological AI advancements. From Drug Discovery to Climate Solutions: The Power of AI Tokens "This is how intelligence is created,” Huang said, introducing the new era of AI development. He explained how AI tokens, the building blocks of intelligent systems, open up endless possibilities. Imagine a future in which AI-assisted drug discovery accelerates the development of life-saving medicines, climate change is mitigated through energy optimization and renewable energy solutions, and personalized education is made available to all as AI tutors adapt to individual learning styles. The RTX 50 Series Unveiled Moving on to hardware, Huang introduced the RTX 50 series, a new powerful GPU designed to accelerate AI workloads. With 92 billion transistors and offering 4,000 TOPS (terabytes of operations per second) for AI, it is three times more powerful than its predecessor, the Ada generation. Huang emphasized its usefulness in both gaming and professional applications: “This RTX 50 Series, Blackwell architecture... the GPU is just a beast,” he said, highlighting its role in real-time computer graphics and AI processing. Driving the Future: NVIDIA's Three-Computer Model for Autonomous Vehicles Huang made important announcements in the area of automotive AI, highlighting NVIDIA's commitment to the automotive industry. He stated: "The autonomous vehicle revolution has arrived. After so many years, with Waymo's success and Tesla's success, it is very, very clear autonomous vehicles have finally arrived.' He predicted that the autonomous vehicle industry is likely to become the first multi-trillion-dollar industry. Huang presented NVIDIA's approach to automotive AI with a 'three-computer' model required to create autonomous vehicles: DGX for training AI models – where AI is trained on huge data sets.
Omniverse for modelling and generating synthetic data – allows you to create digital twins and test scenarios that simulate real driving conditions.
DRIVE AGX, an automotive supercomputer, is designed to deploy AI models for real-time decision-making in cars. Thor: The Next-Gen Automotive Processor A next-generation processor for cars called Thor was announced at CES 2025, which is already in mass production and offers 20 times the processing power of the previous generation Orin. Not only is Thor designed for autonomous vehicles, but it is also a general-purpose robotics computer suitable for a variety of applications, from AMR (autonomous mobile robots) to humanoids. Safety First: NVIDIA Drive OS Meets Highest Safety Standards Huang also highlighted the certification of NVIDIA Drive OS to the highest automotive safety standard, ISO 26262 ASIL-D, which is a significant milestone in automotive safety and AI integration, proudly stating: Drive OS is now the first software-defined programmable AI computer that has been certified up to ASIL D, which is the highest standard of functional safety for automobiles. Partnerships with major automakers such as Toyota, Mercedes, BYD and others were highlighted, demonstrating NVIDIA's integral role in the automotive sector. Toyota was highlighted as a new partner in developing next-generation autonomous vehicles. NVIDIA Cosmos: Understanding the Physical World He also introduced NVIDIA Cosmos, a fundamental model designed to understand the physical world. The model, trained on 20 million hours of video of dynamic physical actions, aims to revolutionize robotics and industrial AI by providing a framework for understanding physical dynamics, with applications ranging from robotics to autonomous vehicles (NVIDIA at CES 2025). Democratizing AI with GeForce Huang emphasized the democratization of AI with NVIDIA hardware, making it accessible to gamers, creators, and enterprises. He said: 'GeForce enabled AI to reach the masses, and now AI is coming home to GeForce,' highlighting NVIDIA's role in the spread of AI. The presentation delved into the evolution of AI from perception to generative capabilities, which are now moving towards 'agent AI' and 'physical AI'. Huang discussed the three laws of scaling that guide the development of AI—scaling before learning, after learning, and during testing—and how they help develop AI capabilities. For example, the law of scaling after learning uses techniques such as reinforcement learning and human feedback to improve AI models. Robotics Reimagined: NVIDIA's Isaac Groot Platform In addition, he introduced NVIDIA's Isaac Groot platform for developing general-purpose robot models, highlighting its use for creating digital twins for robots. “The ChatGPT moment for general robotics is just around the corner," Huang predicted, emphasizing the role of modeling and synthetic data in robotics (NVIDIA Isaac Groot). In conclusion, NVIDIA’s groundbreaking innovations unveiled at CES 2025 mark a bold step toward an AI-driven future, from cigarette pack-sized supercomputers to the evolution of autonomous vehicles. Whether you’re a developer, researcher, or tech enthusiast, these advancements open up new frontiers in computing, robotics, and beyond. Want to stay ahead of the curve? Join the conversation in the comments to discuss how NVIDIA’s latest technologies can transform your industry or project! Speaking at CES on 6 January 2025, Jensen Huang, CEO of NVIDIA, delivered the keynote address from the digitally recreated NVIDIA headquarters, painting a fascinating picture of how artificial intelligence is making impact across industries and everyday life. CES AI in Your Pocket: Introducing NVIDIA Project DIGITS One of the most intriguing announcements was NVIDIA's Project DIGITS, a new AI-powered personal supercomputer. Huang was impressed by its compact design, similar to the 'size of a pack of cigarettes', but capable of delivering a petaflop of computing power. This innovation aims to democratize AI supercomputing by making it accessible to small labs, lone professionals, and even home users ( NVIDIA Project Digits ). petaflop NVIDIA Project Digits Consider a scenario where researchers have access to significant computational resources directly from their workstations. This eliminates dependencies on cloud computing or traditional supercomputers, which can be limited by availability and cost. In this setting, a scientist working in a smaller lab could conduct their research with greater autonomy, utilizing a powerful, localized supercomputer. This accessibility to high-performance computing would enable individual scientists and smaller teams within startups to engage in AI research more readily. This shift could lead to increased research and development activities, as barriers to computational resources are reduced. Data analysis and model training could be performed more quickly and iteratively. Consequently, this future could see more individuals and organizations participating in scientific and technological AI advancements. From Drug Discovery to Climate Solutions: The Power of AI Tokens "This is how intelligence is created,” Huang said, introducing the new era of AI development. He explained how AI tokens, the building blocks of intelligent systems, open up endless possibilities. Imagine a future in which AI-assisted drug discovery accelerates the development of life-saving medicines, climate change is mitigated through energy optimization and renewable energy solutions, and personalized education is made available to all as AI tutors adapt to individual learning styles. The RTX 50 Series Unveiled Moving on to hardware, Huang introduced the RTX 50 series, a new powerful GPU designed to accelerate AI workloads. With 92 billion transistors and offering 4,000 TOPS (terabytes of operations per second) for AI, it is three times more powerful than its predecessor, the Ada generation. Huang emphasized its usefulness in both gaming and professional applications: “This RTX 50 Series, Blackwell architecture... the GPU is just a beast,” he said, highlighting its role in real-time computer graphics and AI processing. Driving the Future: NVIDIA's Three-Computer Model for Autonomous Vehicles Huang made important announcements in the area of automotive AI, highlighting NVIDIA's commitment to the automotive industry. He stated: "The autonomous vehicle revolution has arrived. After so many years, with Waymo's success and Tesla's success, it is very, very clear autonomous vehicles have finally arrived.' He predicted that the autonomous vehicle industry is likely to become the first multi-trillion-dollar industry. Huang presented NVIDIA's approach to automotive AI with a 'three-computer' model required to create autonomous vehicles: DGX for training AI models – where AI is trained on huge data sets. Omniverse for modelling and generating synthetic data – allows you to create digital twins and test scenarios that simulate real driving conditions. DRIVE AGX, an automotive supercomputer, is designed to deploy AI models for real-time decision-making in cars. DGX for training AI models – where AI is trained on huge data sets. DGX for training AI models Omniverse for modelling and generating synthetic data – allows you to create digital twins and test scenarios that simulate real driving conditions. Omniverse for modelling and generating synthetic data DRIVE AGX, an automotive supercomputer , is designed to deploy AI models for real-time decision-making in cars. DRIVE AGX, an automotive supercomputer Thor: The Next-Gen Automotive Processor A next-generation processor for cars called Thor was announced at CES 2025, which is already in mass production and offers 20 times the processing power of the previous generation Orin. Not only is Thor designed for autonomous vehicles, but it is also a general-purpose robotics computer suitable for a variety of applications, from AMR (autonomous mobile robots) to humanoids. Safety First: NVIDIA Drive OS Meets Highest Safety Standards Huang also highlighted the certification of NVIDIA Drive OS to the highest automotive safety standard, ISO 26262 ASIL-D, which is a significant milestone in automotive safety and AI integration, proudly stating: Drive OS is now the first software-defined programmable AI computer that has been certified up to ASIL D, which is the highest standard of functional safety for automobiles. Drive OS is now the first software-defined programmable AI computer that has been certified up to ASIL D, which is the highest standard of functional safety for automobiles. Partnerships with major automakers such as Toyota, Mercedes, BYD and others were highlighted, demonstrating NVIDIA's integral role in the automotive sector. Toyota was highlighted as a new partner in developing next-generation autonomous vehicles. NVIDIA Cosmos: Understanding the Physical World He also introduced NVIDIA Cosmos, a fundamental model designed to understand the physical world. The model, trained on 20 million hours of video of dynamic physical actions, aims to revolutionize robotics and industrial AI by providing a framework for understanding physical dynamics, with applications ranging from robotics to autonomous vehicles ( NVIDIA at CES 2025 ). NVIDIA at CES 2025 Democratizing AI with GeForce Huang emphasized the democratization of AI with NVIDIA hardware, making it accessible to gamers, creators, and enterprises. He said: 'GeForce enabled AI to reach the masses, and now AI is coming home to GeForce,' highlighting NVIDIA's role in the spread of AI. The presentation delved into the evolution of AI from perception to generative capabilities, which are now moving towards ' agent AI' and 'physical AI'. Huang discussed the three laws of scaling that guide the development of AI—scaling before learning, after learning, and during testing—and how they help develop AI capabilities. For example, the law of scaling after learning uses techniques such as reinforcement learning and human feedback to improve AI models. agent AI' Robotics Reimagined: NVIDIA's Isaac Groot Platform In addition, he introduced NVIDIA's Isaac Groot platform for developing general-purpose robot models, highlighting its use for creating digital twins for robots. “The ChatGPT moment for general robotics is just around the corner," Huang predicted, emphasizing the role of modeling and synthetic data in robotics ( NVIDIA Isaac Groot ). NVIDIA Isaac Groot In conclusion, NVIDIA’s groundbreaking innovations unveiled at CES 2025 mark a bold step toward an AI-driven future, from cigarette pack-sized supercomputers to the evolution of autonomous vehicles. Whether you’re a developer, researcher, or tech enthusiast, these advancements open up new frontiers in computing, robotics, and beyond. Want to stay ahead of the curve? Join the conversation in the comments to discuss how NVIDIA’s latest technologies can transform your industry or project! Want to stay ahead of the curve? Join the conversation in the comments to discuss how NVIDIA’s latest technologies can transform your industry or project!

Cigarette Pack-Sized AI Powerhouses and More: NVIDIA's Bold Leap at CES 2025

وحدات ذكاء اصطناعي ضخمة بحجم علبة السجائر وأكثر من ذلك: قفزة جريئة من NVIDIA في معرض CES 2025

Siqaret Paketi Ölçülü Süni İntellekt Gücləri və daha çox: NVIDIA-nın CES 2025-də Cəsarətli Sıçrayışı

Электрастанцыі са штучным інтэлектам памерам з цыгарэтны пачак і многае іншае: смелы скачок NVIDIA на CES 2025

Potencias de inteligencia artificial del tamaño de un paquete de cigarrillos y más: el audaz salto de NVIDIA en el CES 2025

Savukepakkauksen kokoiset tekoälyvoimalaitokset ja paljon muuta: NVIDIAn rohkea harppaus CES 2025 -messuilla

タバコ箱サイズの AI パワーハウスなど: CES 2025 における NVIDIA の大胆な飛躍

Моќни куќи со вештачка интелигенција со големина на пакување цигари и повеќе: Храбриот скок на NVIDIA на CES 2025

सिगरेट प्याक-साइज एआई पावरहाउसहरू र थप: CES 2025 मा NVIDIA को बोल्ड लीप

Potências de IA do tamanho de maços de cigarro e muito mais: o salto ousado da NVIDIA na CES 2025

Výkonné zariadenia AI v balení cigariet a ďalšie: Odvážny skok spoločnosti NVIDIA na veľtrhu CES 2025

Çilim paketli ululykdaky AI güýçleri we beýlekiler: CES 2025-de NVIDIA-nyň batyrgaý böküşi

سگریٹ پیک سائز کے AI پاور ہاؤسز اور مزید: CES 2025 میں NVIDIA کی بولڈ لیپ

Table of Links Abstract and 1. Introduction Abstract and 1. Introduction 2 Data 2.1 Data Sources 2.1 Data Sources 2.2 SS and SI Categories 2.2 SS and SI Categories 3 Methods 3.1 Lexicon Creation and Expansion 3.1 Lexicon Creation and Expansion 3.2 Annotations 3.2 Annotations 3.3 System Description 3.3 System Description 4 Results 4.1 Demographics and 4.2 System Performance 4.1 Demographics and 4.2 System Performance 5 Discussion 5 Discussion 5.1 Limitations 5.1 Limitations 6 Conclusion, Reproducibility, Funding, Acknowledgments, Author Contributions, and References 6 Conclusion, Reproducibility, Funding, Acknowledgments, Author Contributions, and References SUPPLEMENTARY SUPPLEMENTARY Guidelines for Annotating Social Support and Social Isolation in Clinical Notes Guidelines for Annotating Social Support and Social Isolation in Clinical Notes Other Supervised Models Other Supervised Models Abstract Background: Social support (SS) and social isolation (SI) are social determinants of health (SDOH) associated with psychiatric outcomes. In electronic health records (EHRs), individual level SS/SI is typically documented as narrative clinical notes rather than structured coded data. Natural language processing (NLP) algorithms can automate the otherwise labor-intensive process of data extraction. Background Data and Methods: Psychiatric encounter notes from Mount Sinai Health System (MSHS, n=300) and Weill Cornell Medicine (WCM, n=225) were annotated and established a gold standard corpus. A rule-based system (RBS) involving lexicons and a large language model (LLM) using FLAN-T5-XL were developed to identify mentions of SS and SI and their subcategories (e.g., social network, instrumental support, and loneliness). Data and Methods: Results: For extracting SS/SI, the RBS obtained higher macro-averaged f-scores than the LLM at both MSHS (0.89 vs. 0.65) and WCM (0.85 vs. 0.82). For extracting subcategories, the RBS also outperformed the LLM at both MSHS (0.90 vs. 0.62) and WCM (0.82 vs. 0.81). Results Discussion and Conclusion: Unexpectedly, the RBS outperformed the LLMs across all metrics. Intensive review demonstrates that this finding is due to the divergent approach taken by the RBS and LLM. The RBS were designed and refined to follow the same specific rules as the gold standard annotations. Conversely, the LLM were more inclusive with categorization and conformed to common English-language understanding. Both approaches offer advantages and are made available open source for future testing. Discussion and Conclusion: 1 INTRODUCTION Social determinants of health (SDOH) are the non-medical conditions that shape daily life and affect health outcomes [1]. Leveraging SDOH in clinical decision-making may personalize treatment planning and improve patient outcomes [2]. Social support (SS) and social isolation (SI) are two key components of SDOH that significantly impact physical and mental well-being. SI is associated with higher health care expenditure [3], morbidity [4, 5, 6], and mortality [7, 8] and may be as harmful as smoking fifteen cigarettes a day [9]. Specific health risks liked to SI include poor physical and mental well-being [10], metabolic diseases, infectious diseases, dementia [9], suicidal thoughts [11], anxiety [12], and depression [11, 13]. We previously conducted a scoping review to evaluate the relationship between social connectedness and the risk of depression or anxiety and observed that loneliness was significantly associated with higher risks of major depressive disorder, depressive symptom severity, and generalized anxiety disorder [12]. SI comprises several interrelated psychosocial constructs including a lack of a social network, poor emotional support, and feelings of loneliness [14]. The Surgeon General’s 2023 advisory, “Our Epidemic of Loneliness and Isolation,” recommends identification of patients with SI at the health care system level to track community prevalence. Research may then study causal mechanisms, patterns across demographics, and preventive approaches [9]. In contrast, SS and related constructs including emotional support, instrumental support, and social network are associated with improved health outcomes [15, 5, 16]. Social connections facilitate health-related behaviors, including adherence to medication and treatment [17, 18]. Moreover, social relationships are indirectly associated with several aspects relevant to health, such as blood pressure, immune function, and inflammation [19, 20, 21, 22]. In regard to mental health, SS, when measured across a range of settings and populations and using a variety of measures, may be a protective factor for depressive symptoms and disorders [12]. Existing studies on SS and SI are largely based on questionnaire or survey data from small samples or specific populations (e.g., the elderly [13], adolescents during the pandemic [23, 24], and pregnant/postpartum women [12]). Research on identifying SS and SI from real world, large-scale, routinely collected electronic health records (EHRs) is lacking, likely because SDOH information, including SS and SI, are rarely encoded in EHRs as structured data elements [2]. International Classification of Diseases (ICD)-9 V-codes and ICD-10 Z-codes have been expanded to include SI, however, studies note poor adoption rates among clinicians and health systems [25]. Instead, these concepts are often captured in EHRs as part of narrative text during a clinical encounter, yet manual abstraction of such data is time-consuming and labor intensive [26, 2]. Natural language processing (NLP) automates extraction of information from unstructured data and has been implemented in previous literature for identifying different SDOH constructs, including alcohol use, substance use, and homelessness [2]. However, the highly varied language used by clinicians, domain/site-specific knowledge, and lack of annotated data present challenges in extracting SDOH from clinical notes [2]. There are currently three main approaches to extract SS and SI in clinical text, each with strengths and limitations. Note that existing NLP work on SDOH have yet to be optimized for capturing SI/SS. The first approach involves creating dictionaries (“lexicons”) and a set of rules with which to search the text for matches. Lexicons may be either derived from standardized medical ontologies or developed specifically for the task by domain experts. Software may be used to implement the rules, including recognition of negative terms or contexts in which the lexicon match is a false-positive (e.g., if the documented SDOH is not describing the patient, but rather the patient’s sibling). The benefit of this method is that the parameters are highly controlled; there is no “black box” (an inability to see how the model makes decisions) since the pipeline creator is naming exactly what is, or is not, included. However, it is exceedingly difficult to list every term in the lexicon and create a rule for every context in which the term might occur. Previous work using this approach includes studies detecting SI from clinical notes [26, 27] in specific patient populations. ClinicalRegex and Linguamatics I2E, two rule-based/lexicon software, were used to extract SI [28] and SS mentions, again in specific patient populations [29]. Other studies [e.g., Navathe et al. [30]] combine ICD codes with lexicon terms to detect SS/SI. Since the aim of these studies is to identify SS/SI for a clinical purpose, the focus is not on the rigor of algorithm development; therefore, they take more blunt approaches, such as (a) not differentiating between types of SS/SI or considering nuances, (b) using a relatively small sample of manually validated notes, (c) using a single site, and (d) not typically making their pipelines publicly available. The second NLP approach involves traditional training or adapting various machine learning models (pre-packaged topic modeling, deep learning, and language models). EHR-based research has used models trained on a clinical corpus and thus are ideally suited to understand clinical language. However, to perform a task such as identifying specialized concepts like SS/SI, these models still require extensive manually labeled training data to fine-tune the model, which is labor-intensive and generates results that underperform the lexicon-based approach [31]. Finally, an emerging approach is to use large language models (LLMs) which have been trained on massive amounts of data and use transfer learning to perform downstream tasks with little need for fine-tuning or manual labels. The advent of LLMs is a major milestone in the field of NLP and has been used for several tasks in health informatics including SDOH extraction from clinical notes [32, 33]. Preliminary work has used LLMs with minimal fine-tuning to extract SDOH, but the performance of identifying SS/SI has yet to be optimized for clinical or research applications [32]. In summary, each of these approaches for extracting SDOH from clinical text have strengths and limitations. The rule-based system (RBS) requires domain experts and significant time to develop lexicons and rules, which results in highly predictable outputs. In contrast, machine learning and deep learning-based systems rely heavily on a large, annotated corpus for training. Lastly, LLMs need less data for fine-tuning compared to deep learning algorithms, but are often considered black box models, making their decision-making processes less transparent. This work aims to build on these previous systems by breaking down SS/SI into their fine-grained categories including presence/absence of social network, instrumental support, emotional support, and loneliness. This separation is important, as the literature has shown that they are separate concepts [34], not interchangeable, with distinct effects on health outcomes [12]. A general label not only diminishes the signal of detectable associations between subcategories, but also limits the eventual interventions that might come from findings. A distinction is frequently drawn between subjective and objective social support, and they do not necessarily improve together [35]. For example, loneliness is frequently found to be associated with depressive symptoms, but increasing a person’s social activity is not necessarily the way to alleviate loneliness, and other interventions might be more indicated for the individual experiencing loneliness [36]. This study aims to fill a gap in the literature by not only focusing on SS/SI extraction in clinical narratives, but also distinguishing between classes. Here, we describe the development of a rule book for manual annotations as well as rigorous development of a rule-based system (RBS) and an LLM-based system (LLM). Additionally, the variability in clinical documentation, both within and across hospital systems, presents a challenge to the portability of NLP systems [2], and previously published lexicons and pipelines were created for single EHR datasets. An additional aim of this work is to create NLP pipelines that are portable across sites, here, two large academic medical centers in New York City: Mount Sinai Health System [MSHS] and Weill Cornell Medicine [WCM]. By making benchmarked NLP pipelines open source, we aim to enable other healthcare systems to adopt, validate, improve, and deploy the developed SI/SS extraction tool for contextualizing both psychiatric research and clinical practices. This paper is available on arxiv under CC BY 4.0 DEED license. This paper is available on arxiv under CC BY 4.0 DEED license. available on arxiv Authors:
(1) Braja Gopal Patra, Weill Cornell Medicine, New York, NY, USA and co-first authors;
(2) Lauren A. Lepow, Icahn School of Medicine at Mount Sinai, New York, NY, USA and co-first authors;
(3) Praneet Kasi Reddy Jagadeesh Kumar. Weill Cornell Medicine, New York, NY, USA;
(4) Veer Vekaria, Weill Cornell Medicine, New York, NY, USA;
(5) Mohit Manoj Sharma, Weill Cornell Medicine, New York, NY, USA;
(6) Prakash Adekkanattu, Weill Cornell Medicine, New York, NY, USA;
(7) Brian Fennessy, Icahn School of Medicine at Mount Sinai, New York, NY, USA;
(8) Gavin Hynes, Icahn School of Medicine at Mount Sinai, New York, NY, USA;
(9) Isotta Landi, Icahn School of Medicine at Mount Sinai, New York, NY, USA;
(10) Jorge A. Sanchez-Ruiz, Mayo Clinic, Rochester, MN, USA;
(11) Euijung Ryu, Mayo Clinic, Rochester, MN, USA;
(12) Joanna M. Biernacka, Mayo Clinic, Rochester, MN, USA;
(13) Girish N. Nadkarni, Icahn School of Medicine at Mount Sinai, New York, NY, USA;
(14) Ardesheer Talati, Columbia University Vagelos College of Physicians and Surgeons, New York, NY, USA and New York State Psychiatric Institute, New York, NY, USA;
(15) Myrna Weissman, Columbia University Vagelos College of Physicians and Surgeons, New York, NY, USA and New York State Psychiatric Institute, New York, NY, USA;
(16) Mark Olfson, Columbia University Vagelos College of Physicians and Surgeons, New York, NY, USA, New York State Psychiatric Institute, New York, NY, USA, and Columbia University Irving Medical Center, New York, NY, USA;
(17) J. John Mann, Columbia University Irving Medical Center, New York, NY, USA;
(18) Alexander W. Charney, Icahn School of Medicine at Mount Sinai, New York, NY, USA;
(19) Jyotishman Pathak, Weill Cornell Medicine, New York, NY, USA. Authors: Authors: (1) Braja Gopal Patra, Weill Cornell Medicine, New York, NY, USA and co-first authors; (2) Lauren A. Lepow, Icahn School of Medicine at Mount Sinai, New York, NY, USA and co-first authors; (3) Praneet Kasi Reddy Jagadeesh Kumar. Weill Cornell Medicine, New York, NY, USA; (4) Veer Vekaria, Weill Cornell Medicine, New York, NY, USA; (5) Mohit Manoj Sharma, Weill Cornell Medicine, New York, NY, USA; (6) Prakash Adekkanattu, Weill Cornell Medicine, New York, NY, USA; (7) Brian Fennessy, Icahn School of Medicine at Mount Sinai, New York, NY, USA; (8) Gavin Hynes, Icahn School of Medicine at Mount Sinai, New York, NY, USA; (9) Isotta Landi, Icahn School of Medicine at Mount Sinai, New York, NY, USA; (10) Jorge A. Sanchez-Ruiz, Mayo Clinic, Rochester, MN, USA; (11) Euijung Ryu, Mayo Clinic, Rochester, MN, USA; (12) Joanna M. Biernacka, Mayo Clinic, Rochester, MN, USA; (13) Girish N. Nadkarni, Icahn School of Medicine at Mount Sinai, New York, NY, USA; (14) Ardesheer Talati, Columbia University Vagelos College of Physicians and Surgeons, New York, NY, USA and New York State Psychiatric Institute, New York, NY, USA; (15) Myrna Weissman, Columbia University Vagelos College of Physicians and Surgeons, New York, NY, USA and New York State Psychiatric Institute, New York, NY, USA; (16) Mark Olfson, Columbia University Vagelos College of Physicians and Surgeons, New York, NY, USA, New York State Psychiatric Institute, New York, NY, USA, and Columbia University Irving Medical Center, New York, NY, USA; (17) J. John Mann, Columbia University Irving Medical Center, New York, NY, USA; (18) Alexander W. Charney, Icahn School of Medicine at Mount Sinai, New York, NY, USA; (19) Jyotishman Pathak, Weill Cornell Medicine, New York, NY, USA.

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