Jamie Dimon on remote work – JPMorgan Chase CEO Jamie Dimon recently addressed his viral rant on returning to office, apologizing for his language but standing firm on his decision. The controversy started when tech analyst Nicolas Welch questioned the five-day office mandate, leading to ...

Jamie Dimon work-from-home controversy: Jamie Dimon on remote work – Why is the JPMorgan CEO finally putting an end to hybrid work? Here’s what he says - The Economic Times

The company asked Bank of America, HSBC Holdings and JPMorgan Chase to organise a series of fixed-income investor calls on Friday, the report stated, citing a different source. Synopsys, JPMorgan and HSBC did not immediately respond to Reuters' requests for comment, while Bank of America declined ...

Synopsys prepares about $10 billion bond sale to finance Ansys deal, Bloomberg News reports

The JPMorgan Chase CEO has finally opened up about that viral town hall meeting.

Jamie Dimon admits a major mistake after remote work rant leaks - TheStreet

Jamie Dimon, CEO of JPMorgan Chase, is reconsidering remote work due to advancements in VR and AR. These technologies offer immersive environments that mimic physical workspaces, enhancing remote collaboration. AI and machine learning are optimizing remote workflows, addressing productivity ...

Is Jamie Dimon Pioneering a New Era of Remote Work? Why His Latest Moves Could Reshape the Future! - MotoPaddock

The chief executive of JPMorgan Chase made clear to employees this week that when it comes to his policy on remote work, the tradition of petitioning for redress of grievances...

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Jamie Dimon is fed up with remote work: 'I don't care how many people sign that f—ing petition'

Jamie Dimon dismissed employee pleas to ease JPMorgan Chase's five-day office return policy in a recent town hall. He stressed efficiency and reminded staff they have a choice in staying with the company. Dimon criticized remote work for reducing productivity and creativity. Some employees ...

JPMorgan CEO Jamie Dimon derides in-office work pushback, demands efficiency - The Economic Times

US stocks (^DJI,^GSPC, ^IXIC) are surging after a cooler-than-expected core inflation print and following Citigroup (C), JPMorgan Chase (JPM), Wells Fargo (WFC), and Goldman Sachs (GS) reporting strong results, kicking off earnings season in earnest. Quantum computing-related stocks like IonQ ...

Big Bank earnings top estimates, quantum computing stocks rally: Yahoo Finance

JPMorgan Chase

jpmorganchase

JPMC published a in 2021 highlighting their approach to . This article summarizes the problem statement, solution, and other key technical components of the paper* paper Entity Linking What is Entity Linking? It's the task of assigning a to ambiguous mentions of in a text. unique identity named entities Here, “ ” from the text is given a unique identity via a URL (the most common type of ) “ ”. Note that the type of URI used to identify the mentioned entity depends on the domain uniquely. For eg, Instead of a web address, we could have used ISBNs if we were to identify books from a text. Paris URI wikipedia.org/wiki/Paris JPMC was interested in : from to the entities stored in their internal knowledge base (stored as a Mapping mentions of financial institutions news articles Knowledge Graph) An example is shown below: There are two sub-problems that must be defined: : Recognition Extraction of mentions from financial news articles. JPMC has used for this. Spacy : Linking Choosing the correct entity from the internal Knowledge Graph to be linked to the extracted mentions in the previous step. The paper discusses this step. A pictorial representation of this is shown below: String Matching These approaches capture the “morphological” structure of the entity names. The team experimented with (a) Jaccard (b) Levenshtein (c) (also known as ) Ratcliff-Obershelp Gestalt-Pattern-Matching (d) **Jaro Winkler**(e) N-Gram Cosine Similarity The con of these approaches is that they focus just on the “ ” of the names and not the semantics. An example of a failure case would be the matching of “Lumier” and “Lumier”. Even though they are exactly the same, they refer to two different entities. syntactics 2. : Context Similarity Methods These methods take the contexts around mentions and entities to give a similarity score. The Context for “mention” is text to the left and right of the mention, whereas The Context for “entity” is all the data that's stored in the KG for this entity. Finally, Cosine similarity / Jaccard similarity can be used on top of the context vectors. 3. : ML Classification Naive Bayes, Logistic Regression, and SVM are trained on (mention, entity) pairs to find the ones that should be linked 4. Learn to Rank Methods (LTR) These models work in tandem with ML approaches, which might give us multiple (mention, entity) pairs as the solutions. LTR approaches just narrow down to the most probable solution. The idea is to capture both (the meaning that the or stands for) and (character composition of the name) between the names and use a contrastive loss function to train a model. Semantic distance mention entity Syntactic distance We will see below how both of these distances are calculated step by step. Step 1: Obtain embeddings for Entities and Mentions To come up with both of the distances, the authors have proposed to use embeddings for as well as in the KG. mentions entities To obtain , the authors have used a (shown below) embeddings Entity Triplet Loss function For each entity, they used 10 positive and 10 negative samples, making . 10 <entity, positive word, negative word> triplets Unlike embeddings, which they had precomputed, were trained using the on-the-go embeddings approach, where the embedding matrix is learned during the training itself. Entity the embeddings mention Step 2: Calculate Syntactic Distance score Before going further, it's worth mentioning which was introduced by Google in 2016. You can find their official blog . We won’t go into the details, but to give a summary, it's an architecture that has two components — The Wide component and the Deep component. “Wide & Deep” architecture here score calculation is done using the WIDE part, which consists of a Syntactic Distance Linear Siamese Network. The output of the siamese network is the vectors for both the and the which are then compared to find the Euclidean distance. entity mention, Step 3: Calculate Semantic Distance score score calculation is done using the DEEP part Semantic Distance is the pre-trained embedding for the “Apache Corp” that was calculated in Step 1. To obtain the embedding for the , its left and right context words are fed into a Bi-LSTM network that trains the embeddings. The embedding vectors of and the ( are then used to find the Euclidean distance: eₖ mention mention (Vₘ) entity Vₑ) Step 4: Compute Contrastive Loss Both Syntactic and Semantic distances are combined in a weighted fashion as follows: The contrastive loss function is then combined as follows: Contrastive Loss Function where Y is the ground truth value, where a value of 1 indicates that mention m and entity e are matched, 0 otherwise. Combining all the pieces, the final model framework is shown below: At the time of writing this paper, JPMC was still in the process of deploying the model, which, once done, will help support users across JPMC in discovering relevant and curated news that matters to their business. From the cost perspective, not all the mentions are fed through the JEL framework as that would be computationally expensive. JPMC has put another blocking layer to funnel out the mentions that share less than 2 bigrams with the entities from their internal KGs. Once again, is the paper link if you would like to read the full paper. here Also published here Thanks for reading !! Follow Intuitive Shorts (my Substack newsletter), to read quick and intuitive summaries of ML/NLP/DS concepts. You can also follow me on . Medium

Neural Entity Linking and How JPMorgan Chase Plans to Use it

**NEW YORK, United States, March 19th, 2025/Chainwire/--**Arda, a company developing a universal operating system for real estate, has raised $3 million in a pre-seed funding round led by Lightshift. The investment supports Arda’s initiative to enhance efficiency in the $380 trillion real estate sector by addressing its fragmented and opaque infrastructure. Arda is building a digital framework designed to unify real estate assets, data, and financial services into a single, interoperable system. Leveraging AI and blockchain technology, the platform aims to reduce transaction times and enhance transparency by enabling real-time ownership and financial processes. A Purpose-Built Digital Infrastructure for Real Estate Arda’s platform introduces a programmable execution layer for real estate, integrating digital rights management, AI-driven automation, and seamless data interoperability. Key features include: Digital Asset Profiles: A verifiable record of property history to streamline due diligence.
Real-Time Money Movement: Payments directly linked to transactions for improved settlement efficiency.
Integrated Data and Automation: Automated workflows reducing administrative friction in asset management. Digital Asset Profiles: A verifiable record of property history to streamline due diligence. Real-Time Money Movement: Payments directly linked to transactions for improved settlement efficiency. Integrated Data and Automation: Automated workflows reducing administrative friction in asset management. Industry Leadership and Institutional Backing Arda was founded by Oli Harris, former Managing Director in Digital Assets at Goldman Sachs and Head of Crypto Assets Strategy at JPMorgan Chase. Harris played a key role in the development and commercialization of Quorum, an enterprise Ethereum platform, and contributed to institutional digital asset adoption. His experience includes board positions at Anchorage, BitGo, Blockdaemon, and TRM Labs. “Real estate remains one of the most valuable yet operationally fragmented asset classes,” said Oli Harris, Founder & CEO of Arda. “By creating a programmable, trust-based system, we aim to bring real estate transactions in line with modern digital financial infrastructure.” “Real estate remains one of the most valuable yet operationally fragmented asset classes,” said Oli Harris, Founder & CEO of Arda. “By creating a programmable, trust-based system, we aim to bring real estate transactions in line with modern digital financial infrastructure.” A Market Evolving Toward Digitization As institutional investment in digital assets grows, governments and industry leaders are exploring frameworks for secure, verifiable digital property transactions. Regions such as the Gulf are advancing adoption, while U.S. policymakers are shaping regulations to integrate digital assets into mainstream financial systems. “We invest in founders who are building the foundations of next-generation industries,” said Simao Cruz, Founding Partner at Lightshift. “Arda is developing purpose-built infrastructure that could redefine how real estate is owned, transacted, and financed.” “We invest in founders who are building the foundations of next-generation industries,” said Simao Cruz, Founding Partner at Lightshift. “Arda is developing purpose-built infrastructure that could redefine how real estate is owned, transacted, and financed.” About Arda Arda is developing a real estate operating system designed for institutions, enterprises, and governments. Its platform enables digital interoperability, automated transactions, and real-time execution in the global real estate sector. Founded by Oli Harris, Arda is backed by investors supporting the evolution of digital real estate infrastructure. For more information, users can follow @arda_labs on X (Twitter) or contact contact@arda.xyz. About Lightshift Lightshift is a venture firm investing in early-stage companies focused on digital infrastructure and programmable assets. The firm partners with founders to provide capital, technical expertise, and strategic insights for market-defining innovation. Lightshift Lightshift For more information, users can visit www.lightshift.xyz or contact katy.campbell@lightshift.xyz. www.lightshift.xyz www.lightshift.xyz Contact CEO and Founder Oliver Harris Arda oli@arda.xyz This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here here here

Arda Raises Pre-Seed To Build Real Estate’s Operating System,Led By Ex-Goldman MD & JPMC Crypto Head

Arda verhoog Pre-Seed om Real Estate se bedryfstelsel te bou, gelei deur oud-Goldman MD & JPMC Crypto Head

Arda zvyšuje předběžnou přípravu k vybudování operačního systému Real Estate, vedené bývalým Goldmanem MD a krypto hlavou JPMC

Arda recauda capital inicial para construir el sistema operativo inmobiliario, liderado por el exdirector general de Goldman Sachs y el director de criptomonedas de JPMC.

Arda levanta pre-seed para construír o sistema operativo de inmobles, liderado polo ex-Goldman MD e JPMC Crypto Head

Arda、元ゴールドマンMD兼JPMC暗号資産責任者が率いる不動産のオペレーティング システム構築のためにプレシード資金を調達

Arda ຍົກສູງບົດບາດເບື້ອງຕົ້ນເພື່ອສ້າງລະບົບປະຕິບັດງານຂອງອະສັງຫາລິມະສັບ, ນໍາໂດຍ Ex-Goldman MD & JPMC Crypto Head

Арда экс Голдман MD & JPMC Crypto Head тэргүүтэй үл хөдлөх хөрөнгийн үйлдлийн системийг бий болгохын тулд урьдчилсан үрийг өсгөв.

Arda e Godiša Peu ya Pele Go Aga Real Estate’s Operating System,E eteletšwe pele ke Ex-Goldman MD & JPMC Crypto Head

முன்னாள் கோல்ட்மேன் எம்.டி & ஜே.பி.எம்.சி கிரிப்டோ தலைவரால் வழிநடத்தப்படும் ரியல் எஸ்டேட்டின் இயக்க முறைமையை உருவாக்க ஆர்டா முன் விதைகளை திரட்டுகிறது.

ኣርዳ ቅድመ ዘርኢ ኣዕቢዩ ሪል እስቴት’ስ ኦፐሬቲንግ ሲስተም ንምህናጽ፣ብ Ex-Goldman MD & JPMC Crypto Head ዝምራሕ

Arda huy động vốn trước để xây dựng hệ điều hành bất động sản, do cựu giám đốc điều hành Goldman và giám đốc tiền điện tử JPMC dẫn đầu

I-Arda iphakamisa iMbewu yangaphambili ukuze kwakhiwe iNkqubo yokuSebenza ye-Real Estate, ekhokelwa ngu-Ex-Goldman MD kunye ne-JPMC Crypto Head

Although just a fraction of Zelle transfers are fraudulent, the financial losses are still tremendous because so many people use the app. Could a joint effort between big banks and tech companies stop these scams for good? Addressing the Increasing Prevalence of Zelle Scams The peer-to-peer payment app Zelle gives people a fast, easy way to send and receive money. Unfortunately, scammers exploit that convenience. According to the United States Federal Trade Commission, 20% of the people who reported paying a fraudster with a payment app said they used Zelle. On this platform, victims of scams have little recourse. While it typically transfers money in minutes, transactions can happen almost instantaneously. Plus, virtually anyone can create an account. They only need a U.S. phone number or an email address. Unfortunately, it is almost impossible to reverse a Zelle transfer since it pulls money directly from your bank account. It’s not like canceling a check or disputing a charge on a credit card. Once the money’s gone, it’s gone. In July 2024, the Permanent Subcommittee on Investigations (PSI) held an oversight hearing to evaluate how financial institutions and Zelle protected consumers from fraud. During the hearing, Melissa Feldsher — the managing director and head of payments for JPMorgan Chase — said just 0.05% of the transactions made through the bank’s Zelle platform were disputed in 2023. Adam Vancini — the executive vice president for Wells Fargo — similarly said that over 99.9% of Wells Fargo’s Zelle transfers went through without a fraud claim. Months later, the U.S. Consumer Financial Protection Bureau (CFPB) sued JPMorgan Chase, Wells Fargo, and Bank of America, accusing the nation’s three largest banks of failing to protect consumers from peer-to-peer payment scams. It accused them of allegedly allowing scammers to exploit the app’s token system, move between financial institutions, and retain active accounts. As a result, consumers have lost over $870 million since the platform’s release. How Joint Initiatives Between Banks and Tech Firms Help Since this peer-to-peer payment app is owned by Earling Warning Services — a financial tech company co-owned by seven of the largest banks in the U.S. — these institutions have a duty to protect you when you use the app. However, they can’t do it alone. Joint initiatives between financial institutions and tech companies are essential for addressing the increasing prevalence of peer-to-peer payment scams. Why do they need to collaborate? For one, just three banks — JPMorgan Chase, Wells Fargo, and Bank of America —handled about 73% of Zelle transactions in 2023. This peer-to-peer payment platform is inextricably bound to regional financial institutions. The PSI hearing and the CFPB’s lawsuit boil down to a lack of security features and oversight, both of which can be fixed with tech. Today, the big banks mainly focus on working with law enforcement to head off fraudsters before you send them money. However, to stop advanced scamming techniques, they need tech. Know Your Customer (KYC) is an identity verification process. Your banking institution ensures you are who you say you are when you open an account. They check back in periodically just in case you’ve been hacked. With artificial intelligence, KYC becomes incredibly accurate. The advanced fraud detection algorithm can monitor your behaviors — like how you tap, when you open the app, and who you send money to — to verify your identity. Scammers and bots can’t replicate that level of detail. If Zelle, big banks, and AI firms collaborate, they could stop most scams on the platform this way. The Challenges of Adapting to Scamming Techniques In a joint statement to the PSI hearing on Zelle fraud, several bankers' associations argued countering fraudulent activity must be a “cross-industry” effort and “banks cannot stop criminals by themselves.” They said everyone from social media platforms to telecommunications companies to law enforcement has a part to play. While big banks are already taking strides to mitigate malicious activity by investing in tech companies’ technologies, they must do more to prevent fraudsters from creating and using accounts. Keeping them off the platform is crucial because scamming techniques are evolving. For example, with AI, they can make convincing deepfakes or elaborate social engineering scams. If they automate their work with an advanced intelligent algorithm, they could start an enterprise-level fraud ring. Still, even the latest fraud detection tools might not be enough. Sometimes, people are adamant the person they’re sending money to is legitimate, ignoring the red flags. In-depth customer education is just as essential as security tools for securing digital payment platforms. Collaborating to Stop Peer-to-Peer Payment Fraud Identifying fraudulent activity on a platform as widely used as Zelle is no easy feat — especially when scammers have access to much of the same technology as the good guys. Eradicating fraudsters once and for all requires robust, strategic collaboration from banks and tech firms. Although just a fraction of Zelle transfers are fraudulent, the financial losses are still tremendous because so many people use the app. Could a joint effort between big banks and tech companies stop these scams for good? Addressing the Increasing Prevalence of Zelle Scams The peer-to-peer payment app Zelle gives people a fast, easy way to send and receive money. Unfortunately, scammers exploit that convenience. According to the United States Federal Trade Commission, 20% of the people who reported paying a fraudster with a payment app said they used Zelle. 20% of the people 20% of the people On this platform, victims of scams have little recourse. While it typically transfers money in minutes , transactions can happen almost instantaneously. Plus, virtually anyone can create an account. They only need a U.S. phone number or an email address. transfers money in minutes transfers money in minutes Unfortunately, it is almost impossible to reverse a Zelle transfer since it pulls money directly from your bank account. It’s not like canceling a check or disputing a charge on a credit card. Once the money’s gone, it’s gone. impossible to reverse a Zelle transfer impossible to reverse a Zelle transfer In July 2024, the Permanent Subcommittee on Investigations (PSI) held an oversight hearing to evaluate how financial institutions and Zelle protected consumers from fraud. During the hearing, Melissa Feldsher — the managing director and head of payments for JPMorgan Chase — said just 0.05% of the transactions made through the bank’s Zelle platform were disputed in 2023. just 0.05% of the transactions just 0.05% of the transactions Adam Vancini — the executive vice president for Wells Fargo — similarly said that over 99.9% of Wells Fargo’s Zelle transfers went through without a fraud claim. Months later, the U.S. Consumer Financial Protection Bureau (CFPB) sued JPMorgan Chase, Wells Fargo, and Bank of America, accusing the nation’s three largest banks of failing to protect consumers from peer-to-peer payment scams. It accused them of allegedly allowing scammers to exploit the app’s token system, move between financial institutions, and retain active accounts. As a result, consumers have lost over $870 million since the platform’s release. have lost over $870 million have lost over $870 million How Joint Initiatives Between Banks and Tech Firms Help Since this peer-to-peer payment app is owned by Earling Warning Services — a financial tech company co-owned by seven of the largest banks in the U.S. — these institutions have a duty to protect you when you use the app. However, they can’t do it alone. Joint initiatives between financial institutions and tech companies are essential for addressing the increasing prevalence of peer-to-peer payment scams. by seven of the largest banks by seven of the largest banks Why do they need to collaborate? For one, just three banks — JPMorgan Chase, Wells Fargo, and Bank of America — handled about 73% of Zelle transactions in 2023. This peer-to-peer payment platform is inextricably bound to regional financial institutions. handled about 73% of Zelle transactions handled about 73% of Zelle transactions The PSI hearing and the CFPB’s lawsuit boil down to a lack of security features and oversight, both of which can be fixed with tech. Today, the big banks mainly focus on working with law enforcement to head off fraudsters before you send them money. However, to stop advanced scamming techniques, they need tech. Know Your Customer (KYC) is an identity verification process. Your banking institution ensures you are who you say you are when you open an account. They check back in periodically just in case you’ve been hacked. With artificial intelligence, KYC becomes incredibly accurate. The advanced fraud detection algorithm can monitor your behaviors — like how you tap, when you open the app, and who you send money to — to verify your identity. Scammers and bots can’t replicate that level of detail. If Zelle, big banks, and AI firms collaborate, they could stop most scams on the platform this way. The Challenges of Adapting to Scamming Techniques In a joint statement to the PSI hearing on Zelle fraud, several bankers' associations argued countering fraudulent activity must be a “cross-industry” effort and “banks cannot stop criminals by themselves.” They said everyone from social media platforms to telecommunications companies to law enforcement has a part to play. must be a “cross-industry” effort must be a “cross-industry” effort While big banks are already taking strides to mitigate malicious activity by investing in tech companies’ technologies, they must do more to prevent fraudsters from creating and using accounts. Keeping them off the platform is crucial because scamming techniques are evolving. For example, with AI, they can make convincing deepfakes or elaborate social engineering scams. If they automate their work with an advanced intelligent algorithm, they could start an enterprise-level fraud ring. Still, even the latest fraud detection tools might not be enough. Sometimes, people are adamant the person they’re sending money to is legitimate, ignoring the red flags. In-depth customer education is just as essential as security tools for securing digital payment platforms. Collaborating to Stop Peer-to-Peer Payment Fraud Identifying fraudulent activity on a platform as widely used as Zelle is no easy feat — especially when scammers have access to much of the same technology as the good guys. Eradicating fraudsters once and for all requires robust, strategic collaboration from banks and tech firms.

Discover the Collaborative Efforts to Combat Zelle Scams: Banks and Tech

It looks like the whole world has a horse in the 2024 presidential race. Just off the top of my head: the war in Ukraine, the boiling Middle East, the melting EU economy, the China trade deals, and the list of interests and stakes goes on and on. Not to mention countless conspiracy theories, lobbies, predictions, and even aliens. One person can't be the solution for all problems, even if he or she is the 47th President of the United States. But, all the President's men that are going to eventually and inevitably come and follow. Well, that's a different story. It's no wonder we... Can't See AI Problems for the Trees "Show more?" By all means, right away, let's see what's going on here and why AOC is willing to brawl on the FTC hill. Wait! Who's going after the Big Tech? Why? What AI has to do with it? Technically speaking, "Khan's term technically ended this month, though she can stay on as chair until a president replaces her." So, let's just all sit and wait for the President to move around all these chairs. Or, Mark Cuban is afraid that he or she (uh, those damn pronouns) would have a lot on his or her (here they come again) plate from day one in the White House, and this FTC chair could get lost in translation. Cuban is X-ing mixed signals. First, he praised Lina Khan for launching a series of antitrust probes, but then this... The bigger picture is, she’s hurting more than she’s helping. Cuban added that "she had overstepped in taking on technology firms in the AI space." Oh, malice at the AI palace. What exactly are we talking about? It turned out that the FTC "launched a probe of eight companies that offer "surveillance pricing" tools that use artificial intelligence (AI) and other technology to analyze consumer data to help set price targets for products and services. Companies that were ordered by the FTC to provide information for the regulator's study of surveillance pricing include Mastercard, JPMorgan Chase, McKinsey & Co., Accenture, Pros Holdings Inc., Revionics, Bloomreach, and Task Software. The FTC is concerned that "surveillance pricing" could cause consumers to pay higher prices." https://youtu.be/DhrZxSoLmgA?embedable=true Then, there's this. As the Dallas Mavericks minority owner, Cuban has strongly defended the questionable NBA's partnerships with China more than once "despite opposing Chinese and all human rights violations." But, at the same time: Look, I don't follow NBA as I used to, and I'm still exploring AI space, but good luck at trying to explain the concept of global dominance to the guys at the CCP. The "Operation AI Comply," Or Else... "With Operation AI Comply, agency announces five law enforcement actions against operations that use AI hype or sell AI technology that can be used in deceptive and unfair ways." To be more precise, this FTC's Operation includes "actions against a company promoting an AI tool that enabled its customers to create fake reviews, a company claiming to sell “AI Lawyer” services, and multiple companies claiming that they could use AI to help consumers make money through online storefronts." These intentions are good, but it's easy to get lost and misunderstood in the middle of the DOJ's accusations that "Google is a monopolist" and Apple is "violating antitrust laws." If you follow the money, you can't avoid interesting moments and OpenSecrets that these two tech giants are among the top five contributors to the Biden/Harris campaign: Cuban isn't the only major Harris donor who's not comfortable with Khan sitting in the FTC chair. "LinkedIn co-founder Reid Hoffman in July said Khan is “a person who is not helping America,” adding that “antitrust is fine” but that “waging war is not.” IAC Chairman Barry Diller has said he would lobby a Harris Administration to drop Khan." It should be obvious that first, you have to win the Presidential chair to even consider other chairs, including the one reserved for the FTC. Back to AOC and X: "She proves this admin fights for working people. It would be terrible leadership to remove her." Don't count your chickens before the eggs have hatched. I mean, before all votes have been counted. In the meantime, Trump plans to appoint Musk as ‘Secretary of Cost-Cutting.’ There are no brawls in Trump's camp. It looks like the whole world has a horse in the 2024 presidential race. Just off the top of my head: the war in Ukraine, the boiling Middle East, the melting EU economy, the China trade deals, and the list of interests and stakes goes on and on. Not to mention countless conspiracy theories, lobbies, predictions, and even aliens. One person can't be the solution for all problems, even if he or she is the 47th President of the United States. But, all the President's men that are going to eventually and inevitably come and follow. Well, that's a different story. It's no wonder we... Can't See AI Problems for the Trees "Show more?" By all means, right away, let's see what's going on here and why AOC is willing to brawl on the FTC hill. Wait! Who's going after the Big Tech? Why? What AI has to do with it? Technically speaking, "Khan's term technically ended this month, though she can stay on as chair until a president replaces her ." So, let's just all sit and wait for the President to move around all these chairs. Or, Mark Cuban is afraid that he or she (uh, those damn pronouns) would have a lot on his or her (here they come again) plate from day one in the White House, and this FTC chair could get lost in translation. she can stay on as chair until a president replaces her Cuban is X-ing mixed signals. First, he praised Lina Khan for launching a series of antitrust probes, but then this... The bigger picture is, she’s hurting more than she’s helping. The bigger picture is, she’s hurting more than she’s helping. Cuban added that "she had overstepped in taking on technology firms in the AI space." Oh, malice at the AI palace. What exactly are we talking about? overstepped in taking on technology firms It turned out that the FTC "launched a probe of eight companies that offer "surveillance pricing" tools that use artificial intelligence (AI) and other technology to analyze consumer data to help set price targets for products and services. Companies that were ordered by the FTC to provide information for the regulator's study of surveillance pricing include Mastercard, JPMorgan Chase, McKinsey & Co., Accenture, Pros Holdings Inc., Revionics, Bloomreach, and Task Software. The FTC is concerned that "surveillance pricing" could cause consumers to pay higher prices ." FTC is concerned that "surveillance pricing" could cause consumers to pay higher prices https://youtu.be/DhrZxSoLmgA?embedable=true https://youtu.be/DhrZxSoLmgA?embedable=true Then, there's this. As the Dallas Mavericks minority owner, Cuban has strongly defended the questionable NBA's partnerships with China more than once "despite opposing Chinese and all human rights violations." But, at the same time: Look, I don't follow NBA as I used to, and I'm still exploring AI space, but good luck at trying to explain the concept of global dominance to the guys at the CCP. The "Operation AI Comply," Or Else... "With Operation AI Comply , agency announces five law enforcement actions against operations that use AI hype or sell AI technology that can be used in deceptive and unfair ways." Operation AI Comply To be more precise, this FTC's Operation includes "actions against a company promoting an AI tool that enabled its customers to create fake reviews, a company claiming to sell “AI Lawyer” services, and multiple companies claiming that they could use AI to help consumers make money through online storefronts." These intentions are good, but it's easy to get lost and misunderstood in the middle of the DOJ's accusations that "Google is a monopolist " and Apple is "violating antitrust laws ." monopolist antitrust laws If you follow the money, you can't avoid interesting moments and OpenSecrets that these two tech giants are among the top five contributors to the Biden/Harris campaign: OpenSecrets Cuban isn't the only major Harris donor who's not comfortable with Khan sitting in the FTC chair. "LinkedIn co-founder Reid Hoffman in July said Khan is “a person who is not helping America,” adding that “antitrust is fine” but that “waging war is not.” IAC Chairman Barry Diller has said he would lobby a Harris Administration to drop Khan ." lobby a Harris Administration to drop Khan It should be obvious that first, you have to win the Presidential chair to even consider other chairs, including the one reserved for the FTC. Back to AOC and X: "She proves this admin fights for working people. It would be terrible leadership to remove her." Don't count your chickens before the eggs have hatched. I mean, before all votes have been counted. In the meantime, Trump plans to appoint Musk as ‘Secretary of Cost-Cutting .’ There are no brawls in Trump's camp. Trump plans to appoint Musk as ‘Secretary of Cost-Cutting

AOC and FTC vs. AI: What's Going to Happen Next?

9 Cool Case Studies of Global Brands Using LLMs and Generative AI

এলএলএম এবং জেনারেটিভ এআই ব্যবহার করে গ্লোবাল ব্র্যান্ডের 9টি দুর্দান্ত কেস স্টাডি

9 coole Fallstudien globaler Marken, die LLMs und generative KI nutzen

9 estudios de casos interesantes de marcas globales que utilizan LLM e IA generativa

9 études de cas intéressantes de marques mondiales utilisant des LLM et l'IA générative

एलएलएम और जनरेटिव एआई का उपयोग करने वाले वैश्विक ब्रांडों के 9 शानदार केस स्टडीज

LLM と生成 AI を活用したグローバル ブランドの 9 つの優れたケース スタディ

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9 интересных кейсов мировых брендов, использующих LLM и генеративный искусственный интеллект

Yüksek Lisans ve Üretken Yapay Zeka Kullanan Küresel Markalara İlişkin 9 Harika Örnek Olay İncelemesi

9 nghiên cứu điển hình thú vị về các thương hiệu toàn cầu sử dụng LLM và AI sáng tạo

9 个全球品牌使用法学硕士和生成式人工智能的精彩案例研究

Limitations, Ethical Considerations, and More: Everything You Need to Know About WikiWebQuestions

The world of work is changing––rapidly. Thanks to the advent and rapid adoption of generative AI, tech stocks had a bumper 2023, with the share price of the Big Five ( , , , , and ) leaping by 60% from the start of that year. 2023 was also a , which saw its shares triple in price. Alphabet Amazon Apple Meta Microsoft smash success for chipmaker, Nvidia And while adoption isn’t even across the board yet, corporate America is sitting up and taking notice. At JPMorgan Chase, for example, the company said it had 600 machine-learning engineers, with AI working on more than 300 different internal applications. A recent found that 71% of C-suite leaders said that advancing their use of AI is either a high or medium priority for their organization, with 62% of executives noting that they are worried they’re not moving fast enough with AI. study from UKG That has led to some companies doing “AI washing”, aka exaggerating the amount of AI technology they use in their products or services. While some companies might not be entirely truthful about their motivations and use of artificial intelligence or machine learning technologies, what is increasingly true is that in an AI future, tech workers will need to upskill. The World Economic Forum (WEF) says that “the 2020s are becoming the decade of development for employees and employers in terms of skills and career progression”. Its most recent identified that 44% of workers’ skills will be disrupted in the next five years, and six in 10 staff members will require training before 2027. Future of Jobs Report Upskilling for free Key skills to acquire will include new technology capabilities, but the WEF has also identified key human skills such as analytical and creative thinking, as well as resilience, flexibility and agility, motivation, and self-awareness. AKA, the things that artificial intelligence (so far) can’t do. If you’re thinking about some upskilling, then one great place to begin is (OCW) platform. MIT’s OpenCourseWare A free and open space to learn, OCW contains material from thousands of MIT courses across every MIT department and degree program, ranging from the introductory to the most advanced graduate level. Courses include a syllabus, instructional material (such as lecture notes or a reading list), and learning activities like assignments or exams. You can use all the courses at your own pace, and there is no enrollment fee or date to complete by––useful for those working in busy, pressurized roles. A huge range of computer science, engineering, and technology courses are available, across topics such as machine learning, generative AI, Python, deep learning, cognitive robotics, data science, and much more, all for free. If upskilling to get a new job is on your 2024 agenda, then the courses above are a great start. And your job hunt is made far easier too thanks to the . It contains thousands of interesting tech roles, like the three below. HackerNoon Job Board DataAnnotation is seeking a to train its AI chatbots to code. This flexible, part-time or full-time role allows you to choose the projects you want to work on, involves coming up with diverse problems and solutions for a coding chatbot, writing high-quality answers and code snippets, and evaluating the code quality produced by the AI model. You will need to be proficient in at least one programming language and able to solve coding problems (LeetCode, HackerRank). Software Developer Adobe is looking for a in San Jose. The salary range for this position is $135,200 - $250,900, and you will have either research or industry experience in building scalable data and ML platforms. In this role, you will have the opportunity to build a new GenAI foundation to change the creative landscape and will collaborate with data platform engineers and architects to seamlessly integrate low latency data pipelines into the ML platform for model training, as well as writing high quality, product level code that is easy to maintain and test following standard methodologies. Other tasks include designing and implementing reusable and scalable data-loading framework to support video and audio foundational model training in large-scale and distributed environments. Machine Learning Engineer Python programmers looking for a new role can consider this role at SAIC in Chantilly. You’ll be experienced, results-oriented, and mission-driven, with a specialized focus on data engineering in order to perform data model design, data formatting, and ETL development optimized for efficient storage, access, and computation in support of national security objectives. A solid understanding and experience with developing, automating, and enhancing all parts of the data pipeline to include ingestion, processing, storage, and exposing data for consumption is required, along with a focus on improving inefficient tooling and adopting new transformative technologies while maintaining operational continuity. Python Developer Want a great new tech role? Discover it now on the HackerNoon Job Board right By Kirstie McDermott

MIT Has Released a Bunch of Free Courses: Discover 5 To Boost Your Tech Career

এমআইটি একগুচ্ছ বিনামূল্যের কোর্স প্রকাশ করেছে: আপনার কারিগরি ক্যারিয়ারকে উন্নত করতে 5 আবিষ্কার করুন

Das MIT hat eine Reihe kostenloser Kurse veröffentlicht: Entdecken Sie 5, um Ihre Tech-Karriere voranzutreiben

El MIT ha lanzado una serie de cursos gratuitos: descubra 5 para impulsar su carrera tecnológica

Le MIT a publié un certain nombre de cours gratuits : découvrez-en 5 pour booster votre carrière technologique

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MIT가 다양한 무료 강좌를 출시했습니다: 기술 경력을 향상하는 5가지를 찾아보세요

O MIT lançou vários cursos gratuitos: descubra 5 para impulsionar sua carreira tecnológica

MIT выпустил несколько бесплатных курсов: откройте для себя 5, которые помогут улучшить вашу техническую карьеру

MIT Bir Çok Ücretsiz Kurs Yayımladı: Teknoloji Kariyerinizi Yükseltecek 5 Kursu Keşfedin

MIT đã phát hành một loạt khóa học miễn phí: Khám phá 5 khóa học để thúc đẩy sự nghiệp công nghệ của bạn

麻省理工学院发布了一系列免费课程：探索 5 门课程，助你提升科技职业生涯

Exploring Shadow AI's impact on business: risks, strategies, and the quest for a secure, innovative future. How will companies navigate this new frontier? In December 2023, Amazon unveiled its latest venture, Q, promising a safer alternative to consumer-focused chatbots like ChatGPT. However, the excitement was short-lived. Just three days after the announcement, Amazon Q was embroiled in controversy. Employees were alarmed over its inadequate security and privacy measures, revealing that Q fell short of Amazon's stringent corporate standards. Critics its tendency for "hallucinations" and leaking sensitive information, including AWS data center locations, unreleased product features, and internal discount programs. Amazon's engineers were forced into damage control mode, addressing critical issues tagged as a "sev 2" emergency to prevent future fallout. AI highlighted Around the same time, Samsung Electronics Co. grappled with its own AI-induced headache. Sensitive internal source code found its way onto ChatGPT, spotlighting glaring security vulnerabilities. The response was swift: a company-wide ban on generative AI tools was communicated through an internal memo. Samsung's decision underscored the difficulties of managing data on external AI platforms, such as Google Gemini and Microsoft Copilot, where control over data retrieval and deletion is elusive. This move mirrored the concerns of , who viewed these AI services as a digital . Despite the ban's impact on productivity, Samsung remained firm, opting to develop in-house AI solutions for translation, document summarization, and software development until a secure AI-using environment could be established. 65% of Samsung employees Trojan horse Apple, too, joined the fray, prohibiting its employees from using ChatGPT and similar AI-powered tools. The ban was partly fueled by the tools' affiliations with Microsoft, a direct competitor, stoking fears about Apple's sensitive data security. This trend wasn't exclusive to tech giants; financial behemoths like , Deutsche Bank, Wells Fargo, and others also limited AI chatbots' use, aiming to shield sensitive financial information from third-party eyes. JPMorgan Chase Yet, these restrictions inadvertently birthed a culture of "Shadow AI," where employees use their personal devices at work in their quest for efficiency and time-saving, highlighting a significant policy-practice gap in AI usage. Shadow AI: Unseen Threat Although concrete data is scarce, numerous individuals at companies with AI restrictions have to employing such workarounds — those are only the ones open about it! This Shadow AI usage is prevalent in many organizations, encouraging the use of AI in ways that contradict or violate company policies, thus becoming an activity employees feel compelled to conceal. confessed As I dug into this issue deeper, I found some recent studies confirming that despite about in the workplace, . Recent research by Dell that 91% of respondents have dabbled with generative AI in their lives in some capacity, with another 71% reporting they've specifically used it at work. numerous stories companies restricting genAI use employees don't seem to be using it any less indicates The study conducted by highlights a significant gap between AI adoption in the workplace and the formal policies governing its use in Australia and New Zealand. While 63% of employees in these regions utilize AI for various tasks, only 36% of organizations officially allow it. The survey reveals that AI is being applied for creating written content (51%), enhancing productivity (37%), automating repetitive tasks (37%), improving decision-making (29%), and customer service (20%). However, only 11% of organizations have a comprehensive policy for AI usage, and 21% have no intention to establish any. ISACA Moreover, the study by ISACA indicates a lack of AI-related training within organizations, with only 4% offering it to all staff and 57% not providing any training, even to those directly affected by AI technologies. This situation raises concerns similar to those regarding Shadow IT, where employees use IT resources without formal approval, potentially risking organizational security and governance. Navigating the New Frontier of Risk and Responsibility Much like how Shadow IT snuck up on businesses, Shadow AI is already present, forcing organizations to confront their GenAI stance head-on while still figuring out how to use it. Experts guardrails will not stop employees from using AI tools as they significantly enhance productivity and save time. Therefore, company CIOs must confront this issue and explore mitigation strategies that align with their organization's tolerance for risk. Inevitably, employees with good intentions will utilize these tools to increase their efficiency, so corporate tech leaders can prevent any potential harm to the organization by proactively addressing this trend and managing it effectively. believe Every employee's interaction with AI tools can be a potential point of vulnerability. The history of Shadow IT is marked by significant data breaches, such as the infamous incidents involving , which led to the public exposure of the personal data of 30,000 individuals. These historical precedents serve as a cautionary tale, emphasizing the need for rigorous data governance in the age of AI. unsecured Amazon S3 buckets Shadow AI is a more formidable challenge than Shadow IT for several reasons. First, the decentralized nature of AI tool usage means that the potential for data misuse or leakage is not limited to a technical subset of employees (e.g., developers) but extends across the entire organization. Additionally, inherently learn from the data they process, creating a dual layer of risk: the possibility of accessing sensitive data by AI vendors and the enhanced capability of bad actors to discover and exploit exposed data. AIaaS (AI as a Service) models Strategies to Tackle Shadow AI According to , regional VP of EMEA and Asia and head of digital transformation at SAS, tech leaders with a data-first mindset will be able to drive enhanced efficiencies in 2024 and beyond. This is because maximizing the benefits of generative AI tools is contingent upon well-organized data, necessitating robust data management practices encompassing data access, hygiene, and governance. Amir Sohrabi In his for CIO.com, Nick Brackney, Gen AI & Cloud Evangelist Leader at Dell Technologies, points to "three prescriptive ways" businesses should use to combat Shadow AI successfully. article First, establish a centralized strategy for generative AI usage, involving executive leadership to define use cases, create secure access, and protect data. This approach simplifies enforcement and scaling across the organization while requiring effort to build and identify easy wins to ensure success. Second, keep your data organized and understand which types should not be placed in public or hosted private cloud AI offerings, such as trade secrets and sensitive information. Use AI solutions that allow for complete control or do not retain conversation logs for these types of data. Third, control the AI service by bringing it to your data, whether on-premises or through secure cloud solutions, to leverage advantages in governance, employee productivity, and secure data access. This approach enhances the end-user experience, ensuring compliance and reducing the risk of data exposure. Crafting a clear is crucial for delineating improper AI practices that could potentially harm your organization and for guiding the integration of AI applications in line with data security protocols and risk management strategies. This policy serves as a benchmark, allowing decision-makers to evaluate the usage of AI tools within the organization against established guidelines, swiftly pinpoint any risk exposures, and determine the necessary corrective actions. AI Acceptable Use Policy Ethan Mollick, professor at the Wharton School of the University of Pennsylvania, another thought-provoking approach. He believes that traditional methods for integrating new technologies are ineffective for AI due to their centralized nature and slow pace, making it difficult for IT departments to develop competitive in-house AI models or for consultants to provide specific guidance. The real potential for AI application lies with the employees who are experts in their own jobs, suggesting that for organizations to truly benefit from AI, they must engage their workforce (aka "Secret Cyborgs") in using AI technologies. offers First and foremost, brands should acknowledge that employees at any level could possess valuable AI skills, irrespective of their formal role or past performance. Having detected the among their AI-savvy employees, companies must foster a collective learning environment such as crowd-sourced prompt libraries and create a culture that diminishes the apprehension around AI by offering assurances against job loss due to AI, promoting the use of AI for eliminating mundane tasks and encouraging more engaging work. secret cyborgs Establishing psychological safety is crucial to encouraging open AI usage among employees. Employers should be able to offer substantial rewards for identifying significant opportunities where AI can aid the organization. This could include financial incentives, promotions, or flexible working conditions and be handled through gamification. Today's organizations should act swiftly to determine how productivity gains from AI will be utilized, how work processes should be reorganized in light of AI capabilities, and how to manage potential risks associated with AI use, such as data hallucinations and IP concerns. This calls for a proactive approach to crafting comprehensive AI policies, engaging employees across all levels to leverage their insights, and fostering a culture that rewards AI-driven innovation. As technophiles and businesses navigate the complexities of AI integration, what strategies will you deploy to responsibly and innovatively leverage this transformative technology within your organization or personal projects, ensuring a balanced approach to privacy, security, and efficiency? Don’t forget to check out my previous article to discover ! AI’s dirty secret

Shadow AI: Reshaping the Future, But at What Cost?

শ্যাডো এআই: ভবিষ্যতকে পুনর্নির্মাণ করা, কিন্তু কী মূল্যে?

Schatten-KI: Die Zukunft neu gestalten, aber zu welchem Preis?

IA en la sombra: remodelando el futuro, pero ¿a qué precio?

Shadow AI : remodeler l’avenir, mais à quel prix ?

शैडो एआई: भविष्य को नया आकार देना, लेकिन किस कीमत पर?

シャドウ AI: 未来を再構築するが、その代償は?

Shadow AI: 미래를 재편하려면 비용이 얼마나 듭니까?

Shadow AI: remodelando o futuro, mas a que custo?

Теневой ИИ: меняя будущее, но какой ценой?

Shadow AI: Geleceği Yeniden Şekillendirmek, Ama Maliyeti Ne Olacak?

Shadow AI: Định hình lại tương lai, nhưng với cái giá nào?

影子人工智能：重塑未来，但代价是什么？

In the first half of 2023, there was a lot of excitement about investing in technology to achieve impactful enterprise-wide outcomes. However, the practical value of technology enablement doesn't just come from adopting innovations. It's about bringing continuous improvements to the core of company operations and business processes. In 2024, tech executives should approach new technologies with a deliberate and realistic mindset, ensuring each effort serves a purpose and any experiment is purpose-driven. In this article, I’ll analyze and explore how they will impact global businesses. the top 5 enterprise technology trends of 2024 Trend 1: Generative AI Despite polarized opinions and exaggerated hype surrounding generative AI, it will progress beyond offering easy access to complex knowledge and provide new capabilities, including the below. aids accurate budgeting and financial forecasting, empowering enterprises to plan revenue and expenses with greater certainty. Analyzing historical data, GenAI helps identify promising trends for potential profit opportunities. Enhanced asset management. Generative AI GenAI tools automate tedious data entry tasks, streamlining the processing and systemization of large documents within seconds. This enhancement to data processing has around of executives optimistic about boosting productivity across their organizations. Automated data entry. 72% Generative AI contributes to more effective fraud and suspicious activity detection, leading to increased customer satisfaction, improved accuracy, and cost reduction, as demonstrated by JPMorgan Chase. Intelligent fraud detection. Facilitating data management and information retrieval, GenAI enables employees to complete tasks and generate reports more rapidly. Customers benefit from fast and detailed responses to individual queries, bypassing static FAQ pages. Smart contextual search. Combining enterprise databases with generative AI opens new avenues for customer operations, offering hyper-personalization options. Employees can input relevant prompts for models to produce exclusive, specialized texts, visuals, or messaging tailored to specific partner needs. Personalized content generation. The effectiveness of GenAI technology hinges on data quality and the skills of engineers, so it’s important to assemble a strong team of AI strategists and data scientists. They should be capable of developing tailored solutions aligned with an organization's tech and security requirements. Trend 2: ML operations Also called MLOps or industrialized machine learning, machine learning operations refers to the processes and practices that speed up and scale the development of ML models within a company. This includes support, performance monitoring, and continuous improvement. MLOps functions within a system of software and hardware solutions, bringing enhanced value and functionality to enterprises. Industrialized ML helps businesses speed up analytics, identify production issues, and faster. transform PoC projects into products The adoption of industrialized machine learning has surged, and more companies are currently actively investing in MLOps. According to IDC, approximately of businesses are expected to implement industrialized ML by 2024. 60% We can clearly see the shift of ML technology from its pilot stage to a new phase of proactive and decisive adoption. Enterprises are now planning to achieve a competitive advantage through industrialized machine learning—and they are confident about achieving success. Trend 3: Intelligent enterprise apps Gartner predicts that by 2026, approximately of newly developed apps will incorporate AI for 30% better decision-making and personalization. The rise of intelligent apps is explained by the growing use of mobile payment options, wearable apps, and apps with VR and AR features. Modern apps better the UX by ensuring more accurate command execution and providing more detailed analytics, often incorporating AI algorithms and machine learning. So, why are intelligent applications considered valuable for the future of enterprise? AI-powered apps process large volumes of data from various sources and deliver real-time insights to users. Augmented analytics. By omitting irrelevant data, intelligent apps provide leaders with more informative reports, enabling them to make impactful decisions. Efficient decision-making. Such apps assist sales representatives in lead generation and nurturing by scoring leads based on behavior data analysis. Streamlined sales operations. Intelligent apps gather data on business processes and employee performance, identifying opportunities to reduce repetitiveness and enhance employee engagement. Management shortcut discovery. Intelligent software applications are also praised for their continuous improvement capabilities. With ML models and AI algorithms, these apps can adapt to new requirements, updating their output and maintaining high-quality performance. Trend 4: Web3 development Web3 technology finds applications across various sectors from banking, financial services and insurance (BFSI), media, and entertainment to logistics and retail because of the additional trust it provides. Key aspects of web3 adoption include: Web3 shifts power dynamics by giving businesses more control over their assets. The framework emphasizes transparency and equal responsibility among participants. Reduced authority intervention. Web3's focus on transparency opens doors to innovative business models and ensures fairness through automation, smart contracts, and a shared truth source among stakeholders. New business model development. Web3 integration into business requires regulatory frameworks. That’s why early adopters play a key role in normalizing and advocating web3 technology to set the groundwork for rules and standards. Web3 regulations. The increasing investment in decentralized technology stimulates the development of energy-efficient solutions, a crucial step for organizations that want to maximize their potential in industry 4.0 before transitioning to industry 5.0. Trend 5: Cloud computing As businesses shift to the cloud, its influence on current and future enterprise processes remains profound. Here are key innovative directions in which cloud computing is evolving: Integrating edge computing with cloud technology helps organizations reduce data transfer costs, achieve better latency, and reinforce cybersecurity. Combined cloud and edge computing. This strategy benefits developers, fostering workload distribution, cross-department collaboration, and flexibility in costs and investments. Hybrid models. AI-powered tools enhance cloud computing service and security monitoring, providing real-time insights crucial for decision-making and data analytics. This combination has led to the rise of Artificial Intelligence as a Service. AI/ML integration. Businesses will continue investing in expanding internal development teams with professionals having essential cloud computing skills to explore the potential of the latest cloud-powered directions. How do I choose the right direction? Picking the right enterprise technology from the tendencies of 2024 is simpler than it seems. Choosing the most popular trend might not be what defines the future of an enterprise. It's about finding technology that fits the specific needs of a business. Don't hyperfocus on trends. Not all trends stay relevant. Focus on innovations that maintain strong positions over time and offer continuous improvement for long-term value and ROI. Consider the results expected at least five years after implementing technology. Keep reusability in mind. Top enterprise technology trends may seem promising, but the adoption journey is long and complex. Connect wishes to reality by calculating estimated ROI and evaluating potential organizational resistance. Stay realistic. Also published . here

2024 Tech Landscape: 5 Trends Driving Operational Change

Continuous Integration and Continuous Deployment (CI/CD) have become necessary practices in this world where technology is moving fast, but security remains a top concern. CI/CD pipelines are the core of software delivery, but they can also show great weakness when it comes to security. With how complex software development is growing, it is important to have measures that will ensure the safety of . This is where AIOps comes into play, as the secret weapon for CI/CD security. CI/CD pipelines The State of CI/CD Security Understanding the current situation is crucial. CI/CD pipelines face a fair share of security issues due to their continuous nature, involving frequent code changes, builds, tests, and deployments. Here are some common challenges: 1. : Nasty code can sneak into the pipeline and spread through deployments, opening the door to security problems. Code Injection 2. : Sometimes, sensitive data slips out during the CI/CD process, putting user privacy and compliance at risk. Data Leakage 3. : If permissions aren't set up right, it's an open invitation for unauthorized access and potential breaches. Access Control 4. : CI/CD leans on third-party bits, which can carry vulnerabilities that threaten the whole process. Dependency Vulnerabilities With these challenges in mind, taking proactive security steps is a must, and AIOps steps in as the solution. Introduction to AIOps in CI/CD Security AIOps, short for Artificial Intelligence for IT Operations, is an advanced approach that uses artificial intelligence and machine learning to improve various aspects of IT management. In CI/CD security, AIOps plays an important role by offering real-time monitoring, data analysis, predictive analytics, and automated responses to security threats. Here's how AIOps can strengthen security in your CI/CD pipelines. Automated Threat Detection A key aspect of AIOps is its capacity to automatically find security issues in CI/CD pipelines. By constantly monitoring pipeline actions, it can identify deviations from the norm. It checks code changes, the building process, and deployment phases for signs of wrongdoing. If someone attempts to slip in unauthorized code, AIOps promptly detects it and raises a security alert. Real-time Monitoring and Response Security in CI/CD needs constant watchfulness. AIOps is great at this, noticing odd things right when they happen. In a CI/CD setup, this means acting fast in security situations. For instance, if there's an unusual data transfer during deployment, AIOps can trigger alerts and take steps to stop it, preventing possible breaches. Predictive Security Analysis AIOps doesn't only respond at the moment; it's also proactive. Thanks to predictive analytics, it can foresee security problems before they happen. By studying past data and spotting patterns, it can predict possible threats and weak points in the pipeline. This helps security teams take steps ahead of time to keep things safe during the whole CI/CD process. Case Studies: Real-world Success with AIOps in CI/CD Security Now that we've covered the principles of AIOps in CI/CD security, it's essential to see how these principles are applied successfully in the real world. Several organizations have harnessed the power of AIOps to enhance their security in CI/CD pipelines. Here are a few notable companies: Google Amazon Microsoft Netflix Spotify Airbnb Uber Walmart Target Capital One JPMorgan Chase Bank of America These companies are tapping into the power of AIOps to automate security chores, speed up threat detection and fixes, and strengthen the security of their CI/CD pipelines. Take Google, for instance; they're using AIOps to sniff out and tackle security issues in their Kubernetes clusters. Amazon is also on board, using AIOps to automate security checks in their CI/CD pipelines. And Microsoft? They're making use of AIOps to dig into security logs and spot any fishy stuff going on. Implementation Strategies for AIOps in CI/CD Security When it comes to bringing AIOps into CI/CD security, it's a smart move that needs careful planning. Here are some important strategies to keep in mind: 1. : You've got to pick the AIOps tools that fit well with your CI/CD pipeline and security needs. Tool Selection 2. : Make sure that AIOps smoothly blends with your existing CI/CD tools and processes. Integration 3. : Figure out the right levels of monitoring and how you'll respond to security issues tailored to your specific pipeline. Monitoring Thresholds 4. : Train your security and operations teams so they can use AIOps tools effectively and act on responses. Staff Training 5. : Be sure to deal with concerns about data privacy and follow the rules in your industry. AIOps should always operate within legal and regulatory boundaries. Data Privacy and Compliance Benefits of AIOps in CI/CD Security Adopting AIOps into CI/CD security offers several advantages that can significantly impact your software development process: 1. : AIOps makes detecting threats almost instant, speeding up the process of spotting and dealing with potential security issues in your CI/CD pipeline. Swift Threat Detection 2. : Thanks to automation and real-time monitoring, AIOps allows for rapid responses to security incidents, keeping their impact to a minimum. Quick Response Times 3. : AIOps strengthens your overall CI/CD security with its automated threat detection and predictive analysis, lowering the chances of security breaches. Enhanced Overall Security 4. : AIOps can cut operational costs by automating many security tasks, freeing up your teams to focus on more strategic security efforts. Cost Savings 5. : AIOps systems can be set up to ensure compliance with industry standards and regulations, reducing the risk of non-compliance. Enhanced Compliance Challenges and Considerations While AIOps is a powerful ally in CI/CD security, there are some challenges and things to keep in mind: 1. AIOps deals with sensitive data, so safeguarding it and meeting privacy rules is crucial. Data Privacy: 2. : AIOps can sometimes trigger false alarms. It's important to tweak these systems to prevent your security team from being flooded with unnecessary alerts. False Alarms 3. : Setting up and managing AIOps systems requires a certain skill set. You might need training or skilled staff to handle it effectively. Skill Requirements 4. : Getting AIOps to work smoothly with your existing CI/CD tools can be tricky. Planning the integration carefully is a must. Integration Complexity Future Trends and Innovations The future of AIOps in CI/CD security looks bright, with some exciting trends and innovations on the horizon: - : AIOps will increasingly rely on understanding patterns and behavior to spot security threats. Behavior-Based Threat Detection - : AIOps will keep getting better at working smoothly with different CI/CD platforms, making it more adaptable. Cross-Platform Integration - : AIOps will become even smarter at predicting threats, making it more accurate. Enhanced Predictive Analytics , AIOps is like the secret weapon for CI/CD security. Its automated threat detection, real-time monitoring, and predictive analysis are key to keeping your CI/CD pipelines safe and sound. As software development keeps changing, AIOps will play a bigger role in securing the way your software gets delivered. In conclusion The future of CI/CD security depends on those who use AIOps to build secure, reliable, and efficient software delivery pipelines.

AIOps: The Secret Weapon for CI/CD Security

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