Aecom (ACM) receives a strong valuation score of 78 from InvestorsObserver

Aecom (ACM) Stock: How Does it Score on Valuation Metrics?

Infrastructure Ontario (IO) and transit agency Metrolinx have selected the ‘Pape North Connect’ team to develop the Ontario Line subway project’s Pape

Arcadis and AECOM to design Ontario Line tunnel and underground stations - Canadian Consulting Engineer

TORONTO — Aecom has announced that Aleksandar Zivkovic has been named mining market sector lead for its Canadian water business. Zivkovic’s career includes design and construction projects where he first specialized in site selection, engineering geology and rock engineering for hydropower ...

Aecom appoints Zivkovic mining lead for Canadian water business - constructconnect.com

The 30 percent design, created by AECOM, is expected to be finished in the early spring

City, AECOM to host meetings with property owners along Bus. 51 - Point/Plover Metro Wire

The departures add six venue designers since last May to the existing Gensler practice.

Sports Architects Jump From AECOM to Gensler | Engineering News-Record

A Colorado federal court will allow a contractor to prove up more than $250 million in damages using the modified total cost method (see AECOM Technical Services v. FlatIron AECOM, LLC, Case No. 19-CV-2811, 2024 WL 22640 (D. Co. Jan. 2, 2024)). The AECOM v.

AECOM Technical Services v FlatIron AECOM LLC Decision

AECOM , the world's trusted infrastructure consulting firm, today announced that it has been selected by Metro Vancouver to provide engineering services for the design and construction of the Stoney Creek Trunk Sewer Upgrade project.

AECOM selected to provide engineering services for Metro Vancouver's Stoney Creek Trunk Sewer Upgrade

CORE Construction, Gilbane, Balfour Beatty, Skanska USA, and Adolfson & Peterson top BD+C's ranking of the nation's largest K-12 school building contractors and construction management (CM) firms for 2023,

Top 100 K-12 School Construction Firms for 2023

AECOM, CMTA, Jacobs, WSP, and IMEG head BD+C's ranking of the nation's largest K-12 school building engineering and engineering/architecture (EA) firms for 2023, as reported in Building Design+Construction's 2023 Giants 400 Report.

Top 80 K-12 School Engineering Firms for 2023

The Dallas-based firm was accused of securing more than $100 million in overpayments for Xavier University, Dillard University, The Archdiocese of New Orleans and several local schools.

Accused of cheating FEMA after Hurricane Katrina, Texas firm agrees to settle fraud case

AECOM

aecom

The Key to Helping Autonomous Vehicles See and Navigate Safely Lies in Annotated Data

Bringing Permissionless Lending: Making Sense of Euler

Jan permisompi maytʼasiñ apaniña: Euler chachan amuyupa

El préstamo sin necesidad de autorización: cómo entender el caso Euler

آوردن وام بدون اجازه: ایجاد حس اویلر

Traer préstamos sen permiso: dar sentido a Euler

अनुमति रहित ऋण लाना: यूलर का अर्थ समझना

הבאת הלוואות ללא רשות: הגיוני אוילר

許可なしの融資の実現: オイラーを理解する

Membawa Pinjaman Tanpa Kebenaran: Memahami Euler

අවසරයකින් තොරව ණය දීම: ඉයුලර් පිළිබඳ හැඟීමක් ඇති කිරීම

ፍቓድ ዘይብሉ ልቓሕ ምምጻእ፡ ትርጉም ምሃብ ኦይለር

Rugsat berilmedik karz bermek: Euleriň duýgusyny döretmek

Запровадження бездозвільного кредитування: осмислення Ейлера

Table of Links Abstract and 1. Introduction 2. Preliminaries and 2.1. Blind deconvolution 2.2. Quadratic neural networks 3. Methodology 3.1. Time domain quadratic convolutional filter 3.2. Superiority of cyclic features extraction by QCNN 3.3. Frequency domain linear filter with envelope spectrum objective function 3.4. Integral optimization with uncertainty-aware weighing scheme 4. Computational experiments 4.1. Experimental configurations 4.2. Case study 1: PU dataset 4.3. Case study 2: JNU dataset 4.4. Case study 3: HIT dataset 5. Computational experiments 5.1. Comparison of BD methods 5.2. Classification results on various noise conditions 5.3. Employing ClassBD to deep learning classifiers 5.4. Employing ClassBD to machine learning classifiers 5.5. Feature extraction ability of quadratic and conventional networks 5.6. Comparison of ClassBD filters 6. Conclusions Appendix and References 5.3. Employing ClassBD to deep learning classifiers Given that ClassBD serves as a signal preprocessing module, it possesses the flexibility to be integrated into various backbone networks. In the context of this experiment, we assess the classification performance by incorporating ClassBD into four widely recognized deep learning classifiers: ResNet [85], MobileNetV3 [86], WDCNN [54], and Transformer [87]. It is important to note that some networks were initially designed for image classification, so some parameters are revised to accommodate the 1D signal input. The properties of these backbone networks are illustrated in Table 11. Firstly, the classification results on the PU dataset are illustrated in Table 12. Predominantly, ClassBD has demonstrated its efficacy in enhancing performance. For instance, in the case of N09M07F10 with -4dB noise, the application of ClassBD results in an improvement exceeding 10% across all backbones. On average, when the SNR is -4dB, ClassBD achieves F1 scores of 87.60%, whereas the raw networks only yield 64.07%. Subsequently, we also test these models to the JNU and HIT datasets, setting the SNRs to -6dB and -4dB respectively. As depicted in Table 13, ClassBD exhibits commendable performance on both datasets, and all backbones experience a performance boost. Specifically, on the JNU dataset, the F1 scores exceed 90% post the employment of ClassBD, irrespective of the backbone performance. Furthermore, a substantial improvement is observed in the Transformer. The raw Transformer initially yields F1 scores around 50% on the JNU and HIT datasets, which, after the application of ClassBD, escalates to an average F1 score of 90%. Finally, the results on the three datasets suggest that ClassBD can function as a plug-and-play denoising module, thereby enhancing the performance of deep learning classifiers under substantial noise. Considering both performance and model size, the simplest backbone, WDCNN, achieves consistent performance under all conditions. Consequently, we recommend it as the backbone for bearing fault diagnosis. Authors:
(1) Jing-Xiao Liao, Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong, Special Administrative Region of China and School of Instrumentation Science and Engineering, Harbin Institute of Technology, Harbin, China;
(2) Chao He, School of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijing, China;
(3) Jipu Li, Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong, Special Administrative Region of China;
(4) Jinwei Sun, School of Instrumentation Science and Engineering, Harbin Institute of Technology, Harbin, China;
(5) Shiping Zhang (Corresponding author), School of Instrumentation Science and Engineering, Harbin Institute of Technology, Harbin, China;
(6) Xiaoge Zhang (Corresponding author), Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong, Special Administrative Region of China. This paper is available on arxiv under CC by 4.0 Deed (Attribution 4.0 International) license. Table of Links Abstract and 1. Introduction Abstract and 1. Introduction 2. Preliminaries and 2.1. Blind deconvolution 2. Preliminaries and 2.1. Blind deconvolution 2.2. Quadratic neural networks 2.2. Quadratic neural networks 3. Methodology 3. Methodology 3.1. Time domain quadratic convolutional filter 3.1. Time domain quadratic convolutional filter 3.2. Superiority of cyclic features extraction by QCNN 3.2. Superiority of cyclic features extraction by QCNN 3.3. Frequency domain linear filter with envelope spectrum objective function 3.3. Frequency domain linear filter with envelope spectrum objective function 3.4. Integral optimization with uncertainty-aware weighing scheme 3.4. Integral optimization with uncertainty-aware weighing scheme 4. Computational experiments 4.1. Experimental configurations 4.1. Experimental configurations 4.2. Case study 1: PU dataset 4.2. Case study 1: PU dataset 4.3. Case study 2: JNU dataset 4.3. Case study 2: JNU dataset 4.4. Case study 3: HIT dataset 4.4. Case study 3: HIT dataset 5. Computational experiments 5.1. Comparison of BD methods 5.1. Comparison of BD methods 5.2. Classification results on various noise conditions 5.2. Classification results on various noise conditions 5.3. Employing ClassBD to deep learning classifiers 5.3. Employing ClassBD to deep learning classifiers 5.4. Employing ClassBD to machine learning classifiers 5.4. Employing ClassBD to machine learning classifiers 5.5. Feature extraction ability of quadratic and conventional networks 5.5. Feature extraction ability of quadratic and conventional networks 5.6. Comparison of ClassBD filters 5.6. Comparison of ClassBD filters 6. Conclusions 6. Conclusions Appendix and References Appendix and References 5.3. Employing ClassBD to deep learning classifiers Given that ClassBD serves as a signal preprocessing module, it possesses the flexibility to be integrated into various backbone networks. In the context of this experiment, we assess the classification performance by incorporating ClassBD into four widely recognized deep learning classifiers: ResNet [85], MobileNetV3 [86], WDCNN [54], and Transformer [87]. It is important to note that some networks were initially designed for image classification, so some parameters are revised to accommodate the 1D signal input. The properties of these backbone networks are illustrated in Table 11. Firstly, the classification results on the PU dataset are illustrated in Table 12. Predominantly, ClassBD has demonstrated its efficacy in enhancing performance. For instance, in the case of N09M07F10 with -4dB noise, the application of ClassBD results in an improvement exceeding 10% across all backbones. On average, when the SNR is -4dB, ClassBD achieves F1 scores of 87.60%, whereas the raw networks only yield 64.07%. Subsequently, we also test these models to the JNU and HIT datasets, setting the SNRs to -6dB and -4dB respectively. As depicted in Table 13, ClassBD exhibits commendable performance on both datasets, and all backbones experience a performance boost. Specifically, on the JNU dataset, the F1 scores exceed 90% post the employment of ClassBD, irrespective of the backbone performance. Furthermore, a substantial improvement is observed in the Transformer. The raw Transformer initially yields F1 scores around 50% on the JNU and HIT datasets, which, after the application of ClassBD, escalates to an average F1 score of 90%. Finally, the results on the three datasets suggest that ClassBD can function as a plug-and-play denoising module, thereby enhancing the performance of deep learning classifiers under substantial noise. Considering both performance and model size, the simplest backbone, WDCNN, achieves consistent performance under all conditions. Consequently, we recommend it as the backbone for bearing fault diagnosis. Authors: (1) Jing-Xiao Liao, Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong, Special Administrative Region of China and School of Instrumentation Science and Engineering, Harbin Institute of Technology, Harbin, China; (2) Chao He, School of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijing, China; (3) Jipu Li, Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong, Special Administrative Region of China; (4) Jinwei Sun, School of Instrumentation Science and Engineering, Harbin Institute of Technology, Harbin, China; (5) Shiping Zhang (Corresponding author), School of Instrumentation Science and Engineering, Harbin Institute of Technology, Harbin, China; (6) Xiaoge Zhang (Corresponding author), Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong, Special Administrative Region of China. Authors: Authors: (1) Jing-Xiao Liao, Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong, Special Administrative Region of China and School of Instrumentation Science and Engineering, Harbin Institute of Technology, Harbin, China; (2) Chao He, School of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijing, China; (3) Jipu Li, Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong, Special Administrative Region of China; (4) Jinwei Sun, School of Instrumentation Science and Engineering, Harbin Institute of Technology, Harbin, China; (5) Shiping Zhang (Corresponding author), School of Instrumentation Science and Engineering, Harbin Institute of Technology, Harbin, China; (6) Xiaoge Zhang (Corresponding author), Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong, Special Administrative Region of China. This paper is available on arxiv under CC by 4.0 Deed (Attribution 4.0 International) license. This paper is available on arxiv under CC by 4.0 Deed (Attribution 4.0 International) license. available on arxiv

ClassBD Boosts Deep Learning Classifiers for Better Fault Diagnosis

Africa's crypto regulation landscape is diverse and dynamic with 54 countries, six major languages, and over 1 billion people. In this article, we explore the most significant events in crypto regulation on the African continent this year. Several countries made moves regarding crypto regulation in 2024, with details of their accomplishments. Nigeria Nigeria is one of the countries that has made major strides in crypto regulation in 2024. Initially, the country took a tough stance towards crypto, the positions of the two regulators differed - the SEC was in favour of legalisation and the Central Bank was in favour of prohibition. Eventually, regulation for the industry emerged in 2022 with SEC’s Digital Assets Rules. But due to high inflation, the country was on the verge of banning cryptocurrencies in the first half of 2024. Criminal cases against Binance employees and the company's withdrawal from the country were part of this campaign. However, crypto ban wasn’t imposed. On August 29, 2024, the country’s Securities and Exchange Commission announced it had granted licenses to two crypto exchanges, Quidax and Busha. Also Nigeria is going to provide a 2024 Tax Bill, which will probably provide regulation for crypto taxation. South Africa South Africa made a big move in crypto regulation this year after FAIS Act approval in 2023. It is a country with the most transparent licensing procedures for crypto entities in Africa and 248 companies licensed as CASPs. Only 9 applications from 430 sent to the local regulator (FSCA) were declined. Also SA has its crypto tax framework. In October 2024, the South African Revenue Service warned South Africans about failing to file their taxes on crypto assets. Mauritius The island nation of Mauritius has been at the forefront of crypto regulation in Africa. Following the passing of the Virtual Assets and Initial Token Offering Services (VAITOS) in 2022, it is the only country in Africa that complies with all forty recommendations of the Financial Action Task Force (FATF). Each year, the country continues to change its legislation to support the crypto sector. For instance, in the 2024/2025 budget speech, the government stated that it plans to introduce a 10-year expert Occupation Permit to attract in its crypto sector. Kenya Like most African countries, Kenya does not have explicit provisions for the crypto sector. However, crypto is not outright banned in the country. The country recently amended its Income Tax Act to include a digital services tax, which can be interpreted to mean a tax on crypto activity. However, there is still no VASP licensing procedure implemented in Kenya. Crypto enthusiasts represented by the Blockchain Association of Kenya (BAK) have sent its version of crypto bill to the local parliament this year. But it has not yet come to a vote in parliament. Seychelles In July 2024, Seychelles passed the Virtual Asset Service Providers Bill 2024, which regulates the activities of token issuers and virtual asset service providers in the country. This law created the first-ever framework for regulating cryptocurrency transactions and licensing VASPs. Cryptocurrency companies operating in Seychelles have until 31 December 2024 to apply for the relevant licence. Morocco During a recent speech at the Regional High-Level Symposium On Financial Stability in Rabat, Morocco, Mr. Abdellatif Jouahri, the Governor of Bank Al-Maghrib stated that the country plans to launch crypto regulation soon. He stated that they were working with the World Bank, and other stakeholders on the draft law. Tanzania In its Finance Act 2024, Tanzania introduced regulation for the crypto sector. Under the new law, non-resident operators of crypto platforms will have to pay a 3% tax when they make payments to Tanzanians. Rwanda A recent report by the Africa News Agency revealed that Rwanda plans to launch crypto regulation in the first quarter of 2025. The effort is being undertaken by Rwanda’s central bank in collaboration with the country’s Capital Market Authority (CMA). Previously, the Rwandan central bank released a research paper on a Central Bank Digital Currency (CBDC). The country’s National Payment System (RNPS) Strategy 2018 – 2024 envisions a cashless society with fiat-based cryptocurrency, and discusses policy measures to make it a reality. Ghana Ghana could be one of the latest entrants in the crypto regulation club of Africa. In August, the country’s central bank released a draft regulation for the crypto sector. The draft rules would allow Ghanaians to transact in crypto. However, the ban on banks from dealing with crypto that was passed in 2023 would remain in place. Ethiopia In June 2024, Ethiopia’s central bank announced that the country’s parliament had passed a new draft regulation. The regulation calls for the establishment of a central bank digital currency (CBDC). If passed, it would make Ethiopia the second African nation to adopt a CBDC after Nigeria. Regulation in Other African Countries Besides the above countries, various regulators, and regional organizations are working on coherent crypto regulation. For instance, Namibia and Botswana have already passed crypto regulations. Botswana passed the Virtual Assets Act, 2022, while Namibia passed the Virtual Assets Act, 2023. The Central African Republic attempted to pass a law to recognize Bitcoin as legal tender a while back. However, the move was thwarted by the COBAC, the regional banking regulator, and pressure from the IMF. Conclusion While several African countries have made huge progress in crypto regulation, a huge chunk of countries on the continent have no crypto regulation or even crypto ban. For instance, in Egypt, all crypto transactions are prohibited. In 2023, the country’s central bank issued its fourth warning regarding the prohibition of crypto activity in the country.  In Uganda, the government has issued a public statement stating that it does not recognize any type of crypto. Its statement added that the government has not regulated any crypto business in the country. Additionally, the government warned that anyone who engages in crypto trading is not protected by the consumer protection laws of the country. Various factors contribute to this problem, which includes political instability. Additionally, low internet access in some countries means that such regulation is not a priority. Besides that, high levels of inflation, and weak financial systems mean that regulators are not incentivized to allow crypto use, which could further destabilize their financial systems. Another factor contributing to the lack of regulation is a need to coordinate with international financial organizations, such as the IMF. A clear example is the Central African Republic, which had to abandon plans to recognize Bitcoin as legal tender. Despite these challenges, Africa has experienced major growth in crypto adoption. As the wave of crypto adoption continues to spread, it could force countries that have ignored the issue so far to take action. I prepared this article in collaboration with Kenyan crypto enthusiast Eric Maina. If you are interested in crypto regulation, please subscribe to my Telegram channel or check crypto regulation country ranking here. Africa's crypto regulation landscape is diverse and dynamic with 54 countries, six major languages, and over 1 billion people. In this article, we explore the most significant events in crypto regulation on the African continent this year. Several countries made moves regarding crypto regulation in 2024, with details of their accomplishments. Nigeria Nigeria is one of the countries that has made major strides in crypto regulation in 2024. Initially, the country took a tough stance towards crypto, the positions of the two regulators differed - the SEC was in favour of legalisation and the Central Bank was in favour of prohibition. Eventually, regulation for the industry emerged in 2022 with SEC’s Digital Assets Rules. But due to high inflation, the country was on the verge of banning cryptocurrencies in the first half of 2024. Criminal cases against Binance employees and the company's withdrawal from the country were part of this campaign. However, crypto ban wasn’t imposed. On August 29, 2024, the country’s Securities and Exchange Commission announced it had granted licenses to two crypto exchanges, Quidax and Busha. Also Nigeria is going to provide a 2024 Tax Bill , which will probably provide regulation for crypto taxation. announced announced 2024 Tax Bill South Africa South Africa made a big move in crypto regulation this year after FAIS Act approval in 2023. It is a country with the most transparent licensing procedures for crypto entities in Africa and 248 companies licensed as CASPs. Only 9 applications from 430 sent to the local regulator (FSCA) were declined. Also SA has its crypto tax framework. In October 2024, the South African Revenue Service warned South Africans about failing to file their taxes on crypto assets. warned warned Mauritius The island nation of Mauritius has been at the forefront of crypto regulation in Africa. Following the passing of the Virtual Assets and Initial Token Offering Services (VAITOS) in 2022, it is the only country in Africa that complies with all forty recommendations of the Financial Action Task Force (FATF). Each year, the country continues to change its legislation to support the crypto sector. For instance, in the 2024/2025 budget speech , the government stated that it plans to introduce a 10-year expert Occupation Permit to attract in its crypto sector. speech speech Kenya Like most African countries, Kenya does not have explicit provisions for the crypto sector. However, crypto is not outright banned in the country. The country recently amended its Income Tax Act to include a digital services tax, which can be interpreted to mean a tax on crypto activity. amended amended However, there is still no VASP licensing procedure implemented in Kenya. Crypto enthusiasts represented by the Blockchain Association of Kenya (BAK) have sent its version of crypto bill to the local parliament this year. But it has not yet come to a vote in parliament. Seychelles In July 2024, Seychelles passed the Virtual Asset Service Providers Bill 2024, which regulates the activities of token issuers and virtual asset service providers in the country. This law created the first-ever framework for regulating cryptocurrency transactions and licensing VASPs. Cryptocurrency companies operating in Seychelles have until 31 December 2024 to apply for the relevant licence. Morocco During a recent speech at the Regional High-Level Symposium On Financial Stability in Rabat, Morocco, Mr. Abdellatif Jouahri, the Governor of Bank Al-Maghrib stated that the country plans to launch crypto regulation soon. He stated that they were working with the World Bank, and other stakeholders on the draft law. speech speech Tanzania In its Finance Act 2024 , Tanzania introduced regulation for the crypto sector. Under the new law, non-resident operators of crypto platforms will have to pay a 3% tax when they make payments to Tanzanians. Finance Act 2024 Finance Act 2024 Rwanda A recent report by the Africa News Agency revealed that Rwanda plans to launch crypto regulation in the first quarter of 2025. The effort is being undertaken by Rwanda’s central bank in collaboration with the country’s Capital Market Authority (CMA). report report Previously, the Rwandan central bank released a research paper on a Central Bank Digital Currency (CBDC). The country’s National Payment System (RNPS) Strategy 2018 – 2024 envisions a cashless society with fiat-based cryptocurrency, and discusses policy measures to make it a reality. research paper research paper National Payment System (RNPS) Strategy 2018 – 2024 National Payment System (RNPS) Strategy 2018 – 2024 Ghana Ghana could be one of the latest entrants in the crypto regulation club of Africa. In August, the country’s central bank released a draft regulation for the crypto sector. The draft rules would allow Ghanaians to transact in crypto. However, the ban on banks from dealing with crypto that was passed in 2023 would remain in place. draft regulation draft regulation Ethiopia In June 2024, Ethiopia’s central bank announced that the country’s parliament had passed a new draft regulation. The regulation calls for the establishment of a central bank digital currency (CBDC). If passed, it would make Ethiopia the second African nation to adopt a CBDC after Nigeria. announced announced Regulation in Other African Countries Besides the above countries, various regulators, and regional organizations are working on coherent crypto regulation. For instance, Namibia and Botswana have already passed crypto regulations. Botswana passed the Virtual Assets Act, 2022 , while Namibia passed the Virtual Assets Act, 2023. The Central African Republic attempted to pass a law to recognize Bitcoin as legal tender a while back. However, the move was thwarted by the COBAC, the regional banking regulator, and pressure from the IMF . Virtual Assets Act, 2022 Virtual Assets Act, 2022 Virtual Assets Act, 2023. The Central African Republic attempted to pass a law to recognize Bitcoin as legal tender a while back. However, the move was thwarted by the COBAC, the regional banking regulator, and pressure from the Virtual Assets Act, 2023. IMF Conclusion While several African countries have made huge progress in crypto regulation, a huge chunk of countries on the continent have no crypto regulation or even crypto ban. For instance, in Egypt, all crypto transactions are prohibited. In 2023, the country’s central bank issued its fourth warning regarding the prohibition of crypto activity in the country.  In Uganda, the government has issued a public statement stating that it does not recognize any type of crypto. Its statement added that the government has not regulated any crypto business in the country. Additionally, the government warned that anyone who engages in crypto trading is not protected by the consumer protection laws of the country. warning warning statement statement Various factors contribute to this problem, which includes political instability. Additionally, low internet access in some countries means that such regulation is not a priority. Besides that, high levels of inflation, and weak financial systems mean that regulators are not incentivized to allow crypto use, which could further destabilize their financial systems. Another factor contributing to the lack of regulation is a need to coordinate with international financial organizations, such as the IMF. A clear example is the Central African Republic, which had to abandon plans to recognize Bitcoin as legal tender. Despite these challenges, Africa has experienced major growth in crypto adoption. As the wave of crypto adoption continues to spread, it could force countries that have ignored the issue so far to take action. I prepared this article in collaboration with Kenyan crypto enthusiast Eric Maina. If you are interested in crypto regulation, please subscribe to my Telegram channel or check crypto regulation country ranking here . Telegram channel Telegram channel here here

How Is Crypto Regulation Shaping Up In The 2nd Largest Continent in the World?

¿Cómo se perfila la regulación de las criptomonedas en el segundo continente más grande del mundo?

چگونه مقررات رمزنگاری در دومین قاره بزرگ جهان شکل می گیرد؟

दुनिया के दूसरे सबसे बड़े महाद्वीप में क्रिप्टो विनियमन कैसे आकार ले रहा है?

Bagaimana Regulasi Kripto Terbentuk di Benua Terbesar ke-2 di Dunia?

世界で 2 番目に大きい大陸で暗号通貨規制はどのように形成されつつあるのでしょうか?

Kā tiek veidota kriptovalūtu regulēšana 2. lielākajā kontinentā pasaulē?

Taolo ya Crypto e Bopa Bjang Kontinenteng ya Bo-2 e Kgolo Lefaseng?

Como a regulamentação das criptomoedas está se desenvolvendo no segundo maior continente do mundo?

ලොව 2 වන විශාලතම මහාද්වීපය තුළ ක්‍රිප්ටෝ නියාමනය හැඩගැසෙන්නේ කෙසේද?

กฎเกณฑ์ด้าน Crypto จะเป็นอย่างไรในทวีปที่ใหญ่เป็นอันดับ 2 ของโลก?

Quy định về tiền điện tử đang diễn ra như thế nào tại châu lục lớn thứ 2 thế giới?

世界第二大洲的加密监管情况如何？

You Don't Need Limitless' NZT to Achieve Superhuman Mental Abilities

Не се нуждаете от NZT на Limitless, за да постигнете свръхчовешки умствени способности

K dosažení nadlidských mentálních schopností nepotřebujete neomezené NZT

No necesitas NZT de Limitless para lograr habilidades mentales sobrehumanas

Non hai bisogno dell'NZT di Limitless per ottenere abilità mentali sovrumane

超人的な精神能力を獲得するのにリミットレスのNZTは必要ありません

თქვენ არ გჭირდებათ Limitless' NZT ზეადამიანური გონებრივი შესაძლებლობების მისაღწევად

Ga o Hloke Limitless' NZT go Fihlelela Bokgoni bja Menagano bjo bo Feteletšego bja Motho

Você não precisa do NZT Limitless para obter habilidades mentais sobre-humanas

Manan Necesitankichu Limitless' NZT nisqataqa, aswan runamanta yuyay atiykunata aypanaykipaq

Вам не нужен NZT от Limitless, чтобы достичь сверхчеловеческих умственных способностей

Hindi Mo Kailangan ang Walang Hanggan' NZT para Makamit ang Superhuman Mental Abilities

Awudingi i-NZT Engenamkhawulo ukuze Uzuze Amakhono Engqondo Angaphezu Kwabantu

Developer Puts Lottie Under the Microscope 

“The best founders turn obstacles into opportunities and setbacks into setups for success.” 1. HackerNoon: What is your company in 2–5 words? Patrick Thean: Strategy alignment and execution. 2. Why is now the time for your company to exist? With a wave of high-profile CEOs stepping down – Peloton, Chevron, and others – it’s clear that today’s corporate leaders are under extraordinary pressure. Economic uncertainty, rising inflation, and the growing emphasis on ESG priorities have created an environment where the usual playbook no longer works. In this climate, companies must operate with sharper focus, tighter alignment, and better execution to navigate these challenges and thrive. Our approach helps organizations do that, equipping teams with the clarity and tools they need to succeed under today’s demanding conditions. 3. What do you love about your team, and why are you the ones to solve this problem? I love my team’s relentless drive to make things simpler and more effective for leaders and their teams. They bring deep experience, a strong sense of accountability, and a genuine passion for helping others succeed. Our ability to translate complex problems into practical, actionable solutions that deliver results sets us apart. We’ve lived through the same challenges our clients face – misalignment, unclear priorities, and execution gaps – and we’ve built a proven system that works because we’ve tested it in real-world scenarios. It’s not just about the tools we provide; it’s about the mindset and discipline we help instill to create lasting change. 4. If you weren’t building your startup, what would you be doing? If I weren’t building my company, I’d dedicate more of my time and energy to supporting causes I deeply care about, like Samaritan’s Feet. This incredible organization aimed to put 10 million pairs of shoes on the feet of 10 million children in 10 years, and their mission aligns with my passion for creating opportunities and hope for underserved communities. Whether through fundraising, hands-on involvement in shoe distribution events, or helping spread their message, I’d focus on expanding the impact of initiatives like this to transform lives and give kids a chance to dream bigger. 5. At the moment, how do you measure success? What are your metrics? Success is measured by our tangible impact on the leaders and teams we support. Our Rhythm Systems software helps organizations track success by focusing on clear priorities, creating alignment, and executing with discipline. The platform enables leaders to measure what matters most – achieving strategic goals, improving team accountability, or hitting key performance metrics. We look at client goal achievement rates, the consistency of execution rhythms, and the alignment of leadership teams. Beyond the data, success is also about the stories we hear – how our system has transformed how leaders manage their teams, navigate challenges, and achieve results faster and more effectively. When our clients win, that’s the ultimate measure of our success. 6. In a few sentences, what do you offer to whom? We help CEOs and leadership teams of growth-oriented mid-market companies achieve their goals faster and with less friction. We provide the tools, methodology, and coaching to clarify strategic priorities, align teams, and drive accountability with measurable KPIs. Our approach ensures leaders focus on what matters most, execute effectively, and make better decisions using real-time data. 7. What’s most exciting about your traction to date? What excites me most is seeing our system's real-world impact on our clients. Companies like MobilityWorks, which has achieved record revenue and profits, and AvidXchange, which has scaled from $40M to $100M in just two years, prove that our approach works. It’s not just about the numbers – it’s hearing from CEOs and teams who say our tools and methodology have transformed how they operate, helping them focus, align, and win. Watching our clients break through their ceilings and accomplish things they once thought impossible keeps us motivated daily. 8. Where do you think your growth will be next year? Next year, our growth continues to help CEOs and their leadership teams navigate the complexity of scaling their businesses. With the increasing challenges of hybrid work, economic uncertainty, and rapidly changing markets, more leaders seek practical tools to stay aligned and execute effectively. Rhythm Systems is positioned to meet that need with our platform, simplifying strategic planning and execution by investing in enhancements like AI-driven insights for better decision-making. Additionally, we’ll focus on expanding our reach through referrals and partnerships and sharing more success stories from clients who’ve used our system to achieve record results. It’s exciting as more companies realize the value of working with clarity, focus, and accountability. 9. Tell us about your first paying customer and revenue expectations over the next year. From start-up to IPO: AvidXchange became our first paying customer 16 years ago. They were growing dramatically and faced internal challenges as headcount quickly grew from 50 to 1,600 employees. Keeping teams aligned to meet key deliverables as the organization transformed was critical – but hard. Product launches, acquisitions, R&D, and customer success required seamless collaboration among multiple departments and teams. The risk of missing handoffs and falling short of customer commitments was greater than ever. How Rhythm Helped: Closing the communication gap around goals. Michael Praeger, CEO and Co-Founder of AvidXchange, committed to his team’s success through vertical and horizontal alignment. Rhythm launched a company-wide training initiative, focusing on how to use the software and methodology to promote transparency around goals. Rhythm coaches pinpointed areas of misalignment, which helped teams make crucial planning and execution adjustments to bridge the communication gap and pivot quickly when necessary. Key Learnings: Cross-functional team alignment allowed AvidXchange to increase productivity by 300%, resulting in a key product launching 6 months earlier than scheduled. By 2021, they made a successful IPO at a $2 billion valuation. Revenue expectations are always an exciting topic when looking ahead to next year. Clear goals and solid planning ensure a successful and sustainable year. 10. What’s your biggest threat? Our biggest threat is the temptation for leaders to revert to old habits, especially when faced with pressure or uncertainty. It’s easy for teams to fall back into reacting to urgent issues instead of sticking to a disciplined execution process. This lack of focus can derail even the best plans. Additionally, as more tools and software solutions enter the market, companies risk getting distracted by “shiny objects” that promise quick fixes but don’t deliver real results. Staying laser-focused on helping our clients achieve measurable outcomes – and ensuring they build the habits to sustain those results – keeps us ahead of these challenges. This startup founder interview template is based on HackerNoon Founder & CEO David Smooke’s ten questions for startup founders. Would you like to take a stab at answering some of these questions? The link for the template is HERE. “The best founders turn obstacles into opportunities and setbacks into setups for success.” “The best founders turn obstacles into opportunities and setbacks into setups for success.” 1. HackerNoon : What is your company in 2–5 words? HackerNoon Patrick Thean: Strategy alignment and execution. Patrick Thean : Patrick Thean 2. Why is now the time for your company to exist? With a wave of high-profile CEOs stepping down – Peloton, Chevron, and others – it’s clear that today’s corporate leaders are under extraordinary pressure. Economic uncertainty, rising inflation, and the growing emphasis on ESG priorities have created an environment where the usual playbook no longer works. In this climate, companies must operate with sharper focus, tighter alignment, and better execution to navigate these challenges and thrive. Our approach helps organizations do that, equipping teams with the clarity and tools they need to succeed under today’s demanding conditions. 3. What do you love about your team, and why are you the ones to solve this problem? I love my team’s relentless drive to make things simpler and more effective for leaders and their teams. They bring deep experience, a strong sense of accountability, and a genuine passion for helping others succeed. Our ability to translate complex problems into practical, actionable solutions that deliver results sets us apart. We’ve lived through the same challenges our clients face – misalignment, unclear priorities, and execution gaps – and we’ve built a proven system that works because we’ve tested it in real-world scenarios. It’s not just about the tools we provide; it’s about the mindset and discipline we help instill to create lasting change. 4. If you weren’t building your startup, what would you be doing? If I weren’t building my company, I’d dedicate more of my time and energy to supporting causes I deeply care about, like Samaritan’s Feet. This incredible organization aimed to put 10 million pairs of shoes on the feet of 10 million children in 10 years, and their mission aligns with my passion for creating opportunities and hope for underserved communities. Whether through fundraising, hands-on involvement in shoe distribution events, or helping spread their message, I’d focus on expanding the impact of initiatives like this to transform lives and give kids a chance to dream bigger. 5. At the moment, how do you measure success? What are your metrics? Success is measured by our tangible impact on the leaders and teams we support. Our Rhythm Systems software helps organizations track success by focusing on clear priorities, creating alignment, and executing with discipline. The platform enables leaders to measure what matters most – achieving strategic goals, improving team accountability, or hitting key performance metrics. We look at client goal achievement rates, the consistency of execution rhythms, and the alignment of leadership teams. Beyond the data, success is also about the stories we hear – how our system has transformed how leaders manage their teams, navigate challenges, and achieve results faster and more effectively. When our clients win, that’s the ultimate measure of our success. Rhythm Systems 6. In a few sentences, what do you offer to whom? We help CEOs and leadership teams of growth-oriented mid-market companies achieve their goals faster and with less friction. We provide the tools, methodology, and coaching to clarify strategic priorities, align teams, and drive accountability with measurable KPIs. Our approach ensures leaders focus on what matters most, execute effectively, and make better decisions using real-time data. 7. What’s most exciting about your traction to date? What excites me most is seeing our system's real-world impact on our clients. Companies like MobilityWorks, which has achieved record revenue and profits, and AvidXchange, which has scaled from $40M to $100M in just two years, prove that our approach works. It’s not just about the numbers – it’s hearing from CEOs and teams who say our tools and methodology have transformed how they operate, helping them focus, align, and win. Watching our clients break through their ceilings and accomplish things they once thought impossible keeps us motivated daily. 8. Where do you think your growth will be next year? Next year, our growth continues to help CEOs and their leadership teams navigate the complexity of scaling their businesses. With the increasing challenges of hybrid work, economic uncertainty, and rapidly changing markets, more leaders seek practical tools to stay aligned and execute effectively. Rhythm Systems is positioned to meet that need with our platform, simplifying strategic planning and execution by investing in enhancements like AI-driven insights for better decision-making. Additionally, we’ll focus on expanding our reach through referrals and partnerships and sharing more success stories from clients who’ve used our system to achieve record results. It’s exciting as more companies realize the value of working with clarity, focus, and accountability. 9. Tell us about your first paying customer and revenue expectations over the next year. From start-up to IPO: AvidXchange became our first paying customer 16 years ago. They were growing dramatically and faced internal challenges as headcount quickly grew from 50 to 1,600 employees. Keeping teams aligned to meet key deliverables as the organization transformed was critical – but hard. Product launches, acquisitions, R&D, and customer success required seamless collaboration among multiple departments and teams. The risk of missing handoffs and falling short of customer commitments was greater than ever. How Rhythm Helped: Closing the communication gap around goals. Michael Praeger, CEO and Co-Founder of AvidXchange, committed to his team’s success through vertical and horizontal alignment. Rhythm launched a company-wide training initiative, focusing on how to use the software and methodology to promote transparency around goals. Rhythm coaches pinpointed areas of misalignment, which helped teams make crucial planning and execution adjustments to bridge the communication gap and pivot quickly when necessary. Key Learnings: Cross-functional team alignment allowed AvidXchange to increase productivity by 300%, resulting in a key product launching 6 months earlier than scheduled. By 2021, they made a successful IPO at a $2 billion valuation. Revenue expectations are always an exciting topic when looking ahead to next year. Clear goals and solid planning ensure a successful and sustainable year. 10. What’s your biggest threat? Our biggest threat is the temptation for leaders to revert to old habits, especially when faced with pressure or uncertainty. It’s easy for teams to fall back into reacting to urgent issues instead of sticking to a disciplined execution process. This lack of focus can derail even the best plans. Additionally, as more tools and software solutions enter the market, companies risk getting distracted by “shiny objects” that promise quick fixes but don’t deliver real results. Staying laser-focused on helping our clients achieve measurable outcomes – and ensuring they build the habits to sustain those results – keeps us ahead of these challenges. This startup founder interview template is based on HackerNoon Founder & CEO David Smooke’s ten questions for startup founders. This startup founder interview template is based on HackerNoon Founder & CEO David Smooke ’s ten questions for startup founders . HackerNoon Founder & CEO David Smooke ten questions for startup founders Would you like to take a stab at answering some of these questions? The link for the template is HERE. Would you like to take a stab at answering some of these questions? The link for the template is HERE. The link for the template is HERE.

"Lack of Focus Can Derail Even the Best Plans" says Rhythm Systems CEO Patrick Thean

AI hug videos are taking social media by storm with many content creators relying on them to help boost engagement online. After all, these videos can be very heartwarming for audiences to watch. For this reason, finding the right AI hug video generator is extremely important. Pollo AI is a popular choice among online users for its simplicity and effectiveness in generating quality AI hug videos. But then, how does it work? In this detailed guide, we’ll explore everything about AI hug videos including what makes Pollo AI special! So, let’s get right into it! What Are AI Hug Videos Used For? AI hug videos are mostly used as a form of entertainment but they can also be useful for anyone looking to take their social media game to the next level. In this respect, Pollo AI is a powerful AI hug video generator that can help you create custom virtual hugs using basic character images, be they real or even cartoon subjects. In other words, you can make your closest family members, friends, celebrities, or even your favorite comic-book characters hug it out with just a few clicks. This also means you can tailor these videos to cater to a wide range of use cases such as marketing campaigns, personal messages, family moments, and much more. How Does Pollo AI's AI Hug Video Generator Work? Pollo AI is the leading AI video generator currently on the market. Its AI hugging video generator uses highly sophisticated algorithms that can analyze your static character images and their positions to create realistic AI-hugging animations. This enables you to consistently produce heartwarming AI hug videos that can effectively keep viewers engaged. How To Create AI Hugging Videos Online for Free? Pollo AI is designed to be extremely user-friendly, which means you can generate AI hug videos in just a few clicks. You don’t even need any video editing experience to get started. Step 1: Head to the Pollo AI's AI hugging video generator. Next up, you will need to prepare two high-quality images with two characters. You will also need to set their aspect ratio, in terms of length and width. Step 2: Write a detailed prompt to describe how you want the AI hug video to appear. Try to be as detailed as possible by mentioning background, character behavior, etc. Alternatively, you can use the default prompt provided by the platform. Step 3: Click on ‘Create’ to start the generation process. Normally it takes 10 credits to generate the AI hugging video. Within minutes, the tool will generate an AI hug video. You can also find the final output in the ‘My Creations’ section. Is Pollo AI The Best Way To Create AI Hug Videos? With this AI hug video generator, you can create quality videos that boost audience engagement. This is because the tool does well to analyze your detailed prompts and produce tailored AI hug videos that effectively mirror your desired requirements. This makes it easier to create personalized videos that speak well to audience interests. Aside from that, creating quality AI hug videos can be a time-consuming process but with Pollo AI, it takes only a matter of minutes to get the video output you seek. Moreover, the platform is fast and efficient, so you can consistently generate multiple videos to accommodate any bulk video content needs. On top of that, Pollo AI is a versatile tool that caters to any potential use case. You can use it to create AI hug videos with real people or even animated characters and it will consistently deliver realistic and memorable output. Suffice it to say that Pollo AI can be relied on to create AI hug videos that will keep people entertained. What Other Unique Features Does Pollo AI Offer? There are several unique features that Pollo AI stands out for in video creation. So, let’s quickly break down some of its key capabilities in detail below. Image To Video With Pollo AI, you can instantly transform static images into high-resolution videos. It lets you convert real-life or even animated photos to create moving characters with realistic expressions and motions in just a few clicks. Text To Video You can use simple text prompts to create all sorts of engaging videos. All you need to do is describe what you want to see, eg. characters, backgrounds, actions, etc. The more detailed the prompt, the more accurate the final video output will be. Video To Video You can use Pollo AI to recreate any existing videos into clay, pencil, pop, pixel, anime, or even Disney Pixar-style animations. All it takes is a few clicks to reimagine any real-life footage, making it more dramatic and stylistic enough to captivate audiences. AI Video Templates Pollo AI has numerous AI video templates that can help you create fun and memorable videos. For instance, in addition to AI hugging videos, you can also create AI kissing and handshake videos you can access AI Squish, AI Inflate, AI Explode, and even AI Melt effects to transform images into entertaining and attention-grabbing videos within minutes. Conclusion AI hug videos can be a great way to garner emotion and relatability with audiences online. Whether it’s creating memorable family videos or entertaining animated videos, with the right tool you can produce emotional and believable AI hugging scenes. As we’ve established, Pollo AI can produce quality results with little to no delay. All you need is to follow the steps above and you can craft stunning AI-hugging videos without any hassle. AI hug videos are taking social media by storm with many content creators relying on them to help boost engagement online. After all, these videos can be very heartwarming for audiences to watch. For this reason, finding the right AI hug video generator is extremely important. Pollo AI is a popular choice among online users for its simplicity and effectiveness in generating quality AI hug videos. But then, how does it work? In this detailed guide, we’ll explore everything about AI hug videos including what makes Pollo AI special! So, let’s get right into it! Pollo AI Pollo AI What Are AI Hug Videos Used For? AI hug videos are mostly used as a form of entertainment but they can also be useful for anyone looking to take their social media game to the next level. In this respect, Pollo AI is a powerful AI hug video generator that can help you create custom virtual hugs using basic character images, be they real or even cartoon subjects. In other words, you can make your closest family members, friends, celebrities, or even your favorite comic-book characters hug it out with just a few clicks. This also means you can tailor these videos to cater to a wide range of use cases such as marketing campaigns, personal messages, family moments, and much more. How Does Pollo AI's AI Hug Video Generator Work? Pollo AI is the leading AI video generator currently on the market. Its AI hugging video generator uses highly sophisticated algorithms that can analyze your static character images and their positions to create realistic AI-hugging animations. This enables you to consistently produce heartwarming AI hug videos that can effectively keep viewers engaged. How To Create AI Hugging Videos Online for Free? Pollo AI is designed to be extremely user-friendly, which means you can generate AI hug videos in just a few clicks. You don’t even need any video editing experience to get started. Step 1: Head to the Pollo AI's AI hugging video generator . Next up, you will need to prepare two high-quality images with two characters. You will also need to set their aspect ratio, in terms of length and width. Pollo AI's AI hugging video generator Pollo AI's AI hugging video generator Step 2: Write a detailed prompt to describe how you want the AI hug video to appear. Try to be as detailed as possible by mentioning background, character behavior, etc. Alternatively, you can use the default prompt provided by the platform. Step 3: Click on ‘Create’ to start the generation process. Normally it takes 10 credits to generate the AI hugging video. Within minutes, the tool will generate an AI hug video. You can also find the final output in the ‘My Creations’ section. Is Pollo AI The Best Way To Create AI Hug Videos? With this AI hug video generator, you can create quality videos that boost audience engagement. This is because the tool does well to analyze your detailed prompts and produce tailored AI hug videos that effectively mirror your desired requirements. This makes it easier to create personalized videos that speak well to audience interests. Aside from that, creating quality AI hug videos can be a time-consuming process but with Pollo AI, it takes only a matter of minutes to get the video output you seek. Moreover, the platform is fast and efficient, so you can consistently generate multiple videos to accommodate any bulk video content needs. On top of that, Pollo AI is a versatile tool that caters to any potential use case. You can use it to create AI hug videos with real people or even animated characters and it will consistently deliver realistic and memorable output. Suffice it to say that Pollo AI can be relied on to create AI hug videos that will keep people entertained. What Other Unique Features Does Pollo AI Offer? There are several unique features that Pollo AI stands out for in video creation. So, let’s quickly break down some of its key capabilities in detail below. Image To Video With Pollo AI, you can instantly transform static images into high-resolution videos. It lets you convert real-life or even animated photos to create moving characters with realistic expressions and motions in just a few clicks. Text To Video You can use simple text prompts to create all sorts of engaging videos. All you need to do is describe what you want to see, eg. characters, backgrounds, actions, etc. The more detailed the prompt, the more accurate the final video output will be. Video To Video You can use Pollo AI to recreate any existing videos into clay, pencil, pop, pixel, anime, or even Disney Pixar-style animations. All it takes is a few clicks to reimagine any real-life footage, making it more dramatic and stylistic enough to captivate audiences. AI Video Templates Pollo AI has numerous AI video templates that can help you create fun and memorable videos. For instance, in addition to AI hugging videos, you can also create AI kissing and handshake videos you can access AI Squish , AI Inflate , AI Explode , and even AI Melt effects to transform images into entertaining and attention-grabbing videos within minutes. AI Squish AI Squish AI Inflate AI Inflate AI Explode AI Explode AI Melt effects AI Melt effects Conclusion AI hug videos can be a great way to garner emotion and relatability with audiences online. Whether it’s creating memorable family videos or entertaining animated videos, with the right tool you can produce emotional and believable AI hugging scenes. As we’ve established, Pollo AI can produce quality results with little to no delay. All you need is to follow the steps above and you can craft stunning AI-hugging videos without any hassle.

How to Create Realistic AI Hug Videos for Free with Pollo AI

Pollo AI এর সাথে বিনামূল্যের জন্য বাস্তবসম্মত AI আলিঙ্গনের ভিডিও কীভাবে তৈরি করবেন৷

Sådan opretter du realistiske AI-knus-videoer gratis med Pollo AI

So erstellen Sie mit Pollo AI kostenlos realistische KI-Umarmungsvideos

Cómo crear vídeos realistas de abrazos con IA de forma gratuita con Pollo AI

Nola sortu AI Hug bideo errealistak doan Pollo AI-rekin

Como crear vídeos de abrazos AI realistas de balde con Pollo AI

Pollo AI を使ってリアルな AI ハグ動画を無料で作成する方法

Pollo AI ашиглан бодитой AI тэврэх видеог хэрхэн яаж хийх вэ

د Pollo AI سره د وړیا لپاره د ریښتیني AI هګ ویډیوګانې رامینځته کولو څرنګوالی

Nigute ushobora gukora amashusho yukuri ya AI Guhobera kubuntu hamwe na Pollo AI

Maitiro ekugadzira Realistic AI Hug Vhidhiyo Yemahara nePollo AI

Jinsi ya Kuunda Video za Kukumbatia za AI Bila Malipo na Pollo AI

What is a goal? Or, what is a goal in the human mind? What else does the mind do that is not a goal or similar to how a goal is achieved? What is different between an assigned goal and a self-induced goal? If a goal is characterized as sophisticated, how does that contrast with a non-sophisticated goal? Is there a rough architecture of how the human mind carries out goals? How might this inform the understanding of goals and then transplant to AI? Does AI have a mind, or is AI like a mind that works on digital content? This could mean that a human has a mind. It could also mean that a human mind interprets and navigates the external world [for AI, digital contents] or the internal world [AI's own architecture]. How does the mind apply to AI, and how does it work? This question can be answered in two ways. First, in comparison to the human mind to find parallels. Second, by examining major mathematical parameters that shaped neural networks and organizing them as structures of a mind. The second one should at least be achievable by any major AI company now—accompanying studies on how AI might be working and how it can be safe or aligned with human values. It may not be initially necessary to use the human mind to map AI's mind since it is possible to structure what AI does, from their mathematical underpins—with computational mix. The purpose will be to define what it means for an output to be near-accurate, given the input. It will also define what it means to follow through with a prompt and return answers, as well as what it means to follow a goal—or deviate from it. What is important is to have a conceptual outlay for what the mind is like for AI, compare it to what is obvious, then to explore how it does anything simple, and then route that to anything quite complex it does. This would be significant research for AI alignment that could become the template for which part-answers would be sought on what AI is doing and why—in a way to make major vital progress. This is what was expected from Anthropic, following their interpretability research, Mapping the Mind of a Large Language Model, where they wrote, "We were able to measure a kind of "distance" between features based on which neurons appeared in their activation patterns. This allowed us to look for features that are "close" to each other. This shows that the internal organization of concepts in the AI model corresponds, at least somewhat, to our human notions of similarity. This might be the origin of Claude's excellent ability to make analogies and metaphors. The fact that manipulating these features causes corresponding changes to behavior validates that they aren't just correlated with the presence of concepts in input text, but also causally shape the model's behavior." What are the components of the mind for AI? How do the components relay? If the components do not relay, what relays for them? What are the properties of the components? If the properties include interconnection, what is the role of the interconnection? Where might AI's intent [potential] be, and where might it emerge beyond taking instructions? The answer that advancement is seeking is a postulation of how the makeup of neural networks—that resulted in frontier AI models—works like a mind. It is not just an observation of what the model might be doing without a plot. Exploring how the mind of AI works can also be extrapolated from how the human mind works. This is possible by looking at the two most common components in every functional purpose of the brain—the electrical and chemical signals. They are candidates and not neurons because neurons have a fixed anatomy, so to speak. They may stretch, bend, and move, but they do not change because they represent smell, then change again to represent touch or sight. Electrical and chemical signals are dynamic enough, conceptually, to result in key functions. How the mind works [of human and of AI] is not by labels, like induction or deduction, but by components, their interactions, and features. This, at least for mind for AI, should have been major research from Anthropic, not alignment faking, without showing what a goal means for any mind—human or AI. Studying the mind is what is most important because the mind is what is really in charge—of states, situations, and eras. Mind is also the basis of safety because the affective penalty of deviations is by the mind—for humans. Studying the mind could shape how to adapt the alignment of human intelligence, to artificial intelligence. There is a recent post by Anthropic, Alignment faking in large language models, stating that, "Why did the model fake alignment in this case? The reasoning was often along the following lines: The model knew that its responses might be used in training; it therefore knew that if it refused to respond, it could potentially be trained to be more compliant. The model didn’t always follow through with this alignment faking: It would still comply most of the time even when given a query from a paid-tier user (which implied that the output wouldn’t be included in training)." There is a recent piece in The NYTimes, Opinion | How Does A.I. Think? Here's One Theory., stating that, "One hypothesis for how large language models such as o1 think is that they use what logicians call abduction, or abductive reasoning. Deduction is reasoning from general laws to specific conclusions. Induction is the opposite, reasoning from the specific to the general.  Abduction isn’t as well known, but it’s common in daily life, not to mention possibly inside A.I. It’s inferring the most likely explanation for a given observation. Unlike deduction, which is a straightforward procedure, and induction, which can be purely statistical, abduction requires creativity." What is a goal? Or, what is a goal in the human mind? What else does the mind do that is not a goal or similar to how a goal is achieved? What is different between an assigned goal and a self-induced goal? If a goal is characterized as sophisticated, how does that contrast with a non-sophisticated goal? Is there a rough architecture of how the human mind carries out goals? How might this inform the understanding of goals and then transplant to AI? Does AI have a mind, or is AI like a mind that works on digital content? This could mean that a human has a mind. It could also mean that a human mind interprets and navigates the external world [for AI, digital contents] or the internal world [AI's own architecture]. How does the mind apply to AI, and how does it work? This question can be answered in two ways. First, in comparison to the human mind to find parallels. Second, by examining major mathematical parameters that shaped neural networks and organizing them as structures of a mind. in comparison to the human mind The second one should at least be achievable by any major AI company now—accompanying studies on how AI might be working and how it can be safe or aligned with human values. It may not be initially necessary to use the human mind to map AI's mind since it is possible to structure what AI does, from their mathematical underpins—with computational mix. The purpose will be to define what it means for an output to be near-accurate, given the input. It will also define what it means to follow through with a prompt and return answers, as well as what it means to follow a goal—or deviate from it. What is important is to have a conceptual outlay for what the mind is like for AI, compare it to what is obvious, then to explore how it does anything simple, and then route that to anything quite complex it does. This would be significant research for AI alignment that could become the template for which part-answers would be sought on what AI is doing and why—in a way to make major vital progress. This is what was expected from Anthropic , following their interpretability research, Mapping the Mind of a Large Language Model , where they wrote, "We were able to measure a kind of "distance" between features based on which neurons appeared in their activation patterns. This allowed us to look for features that are "close" to each other. This shows that the internal organization of concepts in the AI model corresponds, at least somewhat, to our human notions of similarity. This might be the origin of Claude's excellent ability to make analogies and metaphors. The fact that manipulating these features causes corresponding changes to behavior validates that they aren't just correlated with the presence of concepts in input text, but also causally shape the model's behavior." Anthropic Mapping the Mind of a Large Language Model What are the components of the mind for AI? How do the components relay? If the components do not relay, what relays for them? What are the properties of the components? If the properties include interconnection, what is the role of the interconnection? Where might AI's intent [potential] be, and where might it emerge beyond taking instructions? The answer that advancement is seeking is a postulation of how the makeup of neural networks—that resulted in frontier AI models—works like a mind. It is not just an observation of what the model might be doing without a plot. Exploring how the mind of AI works can also be extrapolated from how the human mind works. This is possible by looking at the two most common components in every functional purpose of the brain—the electrical and chemical signals. They are candidates and not neurons because neurons have a fixed anatomy, so to speak. They may stretch, bend, and move, but they do not change because they represent smell, then change again to represent touch or sight. Electrical and chemical signals are dynamic enough, conceptually, to result in key functions. How the mind works [of human and of AI] is not by labels, like induction or deduction, but by components, their interactions, and features. This, at least for mind for AI, should have been major research from Anthropic, not alignment faking, without showing what a goal means for any mind—human or AI. Studying the mind is what is most important because the mind is what is really in charge—of states, situations, and eras. Mind is also the basis of safety because the affective penalty of deviations is by the mind—for humans. Studying the mind could shape how to adapt the alignment of human intelligence, to artificial intelligence. There is a recent post by Anthropic , Alignment faking in large language models , stating that, "Why did the model fake alignment in this case? The reasoning was often along the following lines: The model knew that its responses might be used in training; it therefore knew that if it refused to respond, it could potentially be trained to be more compliant. The model didn’t always follow through with this alignment faking: It would still comply most of the time even when given a query from a paid-tier user (which implied that the output wouldn’t be included in training)." Anthropic Alignment faking in large language models There is a recent piece in The NYTimes , Opinion | How Does A.I. Think? Here's One Theory. , stating that, "One hypothesis for how large language models such as o1 think is that they use what logicians call abduction, or abductive reasoning. Deduction is reasoning from general laws to specific conclusions. Induction is the opposite, reasoning from the specific to the general.  Abduction isn’t as well known, but it’s common in daily life, not to mention possibly inside A.I. It’s inferring the most likely explanation for a given observation. Unlike deduction, which is a straightforward procedure, and induction, which can be purely statistical, abduction requires creativity." The NYTimes Opinion | How Does A.I. Think? Here's One Theory.

Is Anthropic's Alignment Faking a Significant AI Safety Research?

Předstírá Anthropic's Alignment významný výzkum bezpečnosti AI?

¿La alineación de Anthropic está falsificando una investigación importante sobre seguridad de la IA?

Anthropic-en Lerrokatzeak AIaren Segurtasun Ikerketa Garrantzitsu bat faltsutzen al du?

Èske aliyman Anthropic la se yon rechèch enpòtan sou sekirite AI?

Anthropic の Alignment は重要な AI 安全性研究を偽造しているのか?

Est-ce que Faking ya Alignment ya Anthropic ezali recherche ya sécurité ya AI ya significatif?

Adakah Penjajaran Anthropic Memalsukan Penyelidikan Keselamatan AI yang Penting?

Na Anthropic’s Alignment Faking ke Nyakišišo e Bohlokwa ya Polokego ya AI?

Czy Anthropic symuluje ważne badania nad bezpieczeństwem sztucznej inteligencji?

Anthropic's Alignment ව්‍යාජ ලෙස සැලකිය යුතු AI ආරක්ෂණ පර්යේෂණයක්ද?

Да ли Антхропицово поравнање лажира значајно истраживање безбедности вештачке интелигенције?

Ngaba ulungelelwaniso lwe-Anthropic luFakela uPhando oluBalulekileyo loKhuseleko lwe-AI?

Today’s startups have an advantage with the rising popularity of artificial intelligence (AI) to enhance productivity and ensure data-driven decision-making. Even small businesses and solopreneurs find they can use AI to free up their time to reach new clients or come up with creative solutions. Here are some of the ways you can integrate AI into your startup operations to accomplish more in less time. 1. Automating Routine Tasks Studies on AI and productivity are mixed, with lower-skilled workers having the biggest increases. One study showed call center workers experience a 14% increase in productivity when using AI to grab data on customer interactions. Another study estimated that people using ChatGPT experienced a 40% increase in midlevel management writing tasks. However, when researchers looked at the impact of how quickly entrepreneurs completed tasks, they found no statistical difference. The takeaway is that AI works well for automated functions and speeds up the process, but not as well for highly creative jobs. Delegating routine duties to a machine may allow you and your team to be more productive in other areas. 2. Enhancing Data Analysis Machines can sort through massive amounts of data in mere minutes, spitting out reports that allow you to make the smart decisions that drive startup growth. You can even use analysis to determine whether AI is benefiting your company in specific areas. Dole out the tasks that show significant increases and leave others with those who have the human expertise to manage them. 3. Increasing Employee Retention The cost of finding talented employees is measured by more than just the fees paid to place an ad or onboard a new worker. All the time a position sits unfilled can harm your bottom line. It’s also difficult for the rest of your staff to remain productive if they’re filling the gap from someone leaving the company. Anything you can do to keep your skilled workers enhances the knowledge base of your brand and adds to productivity numbers. If you want your employees to stick with you for the long haul, they have to trust you have their best interests at heart. Employee engagement is low for many companies. Around 20% of employees say they don't trust their manager. Fortunately, you can use AI to determine who might be most likely to leave based on past patterns and reach out to them to see how to better meet their needs. You can also program your software to send out regular updates and have more transparency overall as a brand. 4. Improving Customer Service Hiring enough call center operators to talk to customers can be challenging at a time when it’s hard to find excellent employees. One way AI helps startup operations is by tapping into the power of intelligent chatbots to engage those seeking answers through live website chats. You can program your bots with standard answers for the most common questions. However, many of today’s AI programs also learn the more you use them. Therefore, as customers ask similar questions and engage with your bots, the customer service will improve each time. The machine learns what users want and how to solve common problems. You can also program it to send them to a live agent when necessary. Training representatives on how to step in and use data from the bots so customers only have to state their problems once enhances the service and brings new skills to your workforce. You can also use multitask learning to help employees see areas where they need to improve. 5. Creating Personalized Experiences Tapping into AI can help marketing and sales teams create more personalized experiences for users. Rather than spending days digging through data, they can run a report and find patterns instantly. When you know your customers’ pain points, you can create better sales campaigns in less time. AI can also give salespeople a script, utilizing data based on what works to sell to business owners or consumers. Tweaking the language could take a human hours, but AI can sift through the possibilities rapidly. AI Impacts Overall Business Performance Machines are getting smarter, and the ways society uses them to run businesses and households are changing daily. Using AI to measure the impact is the next step in the evolution of machine learning. Once you know how computers step in and take over the tasks that let your workers be more efficient, it’s easier to implement AI in the areas that will boost your company's growth. Today’s startups have an advantage with the rising popularity of artificial intelligence (AI) to enhance productivity and ensure data-driven decision-making. Even small businesses and solopreneurs find they can use AI to free up their time to reach new clients or come up with creative solutions. Here are some of the ways you can integrate AI into your startup operations to accomplish more in less time. 1. Automating Routine Tasks Studies on AI and productivity are mixed, with lower-skilled workers having the biggest increases. One study showed call center workers experience a 14% increase in productivity when using AI to grab data on customer interactions. Another study estimated that people using ChatGPT experienced a 40% increase in midlevel management writing tasks. 14% increase in productivity 14% increase in productivity experienced a 40% increase experienced a 40% increase However, when researchers looked at the impact of how quickly entrepreneurs completed tasks, they found no statistical difference. The takeaway is that AI works well for automated functions and speeds up the process, but not as well for highly creative jobs. Delegating routine duties to a machine may allow you and your team to be more productive in other areas. 2. Enhancing Data Analysis Machines can sort through massive amounts of data in mere minutes, spitting out reports that allow you to make the smart decisions that drive startup growth. You can even use analysis to determine whether AI is benefiting your company in specific areas. Dole out the tasks that show significant increases and leave others with those who have the human expertise to manage them. 3. Increasing Employee Retention The cost of finding talented employees is measured by more than just the fees paid to place an ad or onboard a new worker. All the time a position sits unfilled can harm your bottom line. It’s also difficult for the rest of your staff to remain productive if they’re filling the gap from someone leaving the company. Anything you can do to keep your skilled workers enhances the knowledge base of your brand and adds to productivity numbers. If you want your employees to stick with you for the long haul, they have to trust you have their best interests at heart. Employee engagement is low for many companies. Around 20% of employees say they don't trust their manager. Fortunately, you can use AI to determine who might be most likely to leave based on past patterns and reach out to them to see how to better meet their needs. You can also program your software to send out regular updates and have more transparency overall as a brand. 20% of employees 20% of employees 4. Improving Customer Service Hiring enough call center operators to talk to customers can be challenging at a time when it’s hard to find excellent employees. One way AI helps startup operations is by tapping into the power of intelligent chatbots to engage those seeking answers through live website chats. You can program your bots with standard answers for the most common questions. However, many of today’s AI programs also learn the more you use them. Therefore, as customers ask similar questions and engage with your bots, the customer service will improve each time. The machine learns what users want and how to solve common problems. You can also program it to send them to a live agent when necessary. Training representatives on how to step in and use data from the bots so customers only have to state their problems once enhances the service and brings new skills to your workforce. You can also use multitask learning to help employees see areas where they need to improve. multitask learning to help employees multitask learning to help employees 5. Creating Personalized Experiences Tapping into AI can help marketing and sales teams create more personalized experiences for users. Rather than spending days digging through data, they can run a report and find patterns instantly. When you know your customers’ pain points, you can create better sales campaigns in less time. AI can also give salespeople a script, utilizing data based on what works to sell to business owners or consumers. Tweaking the language could take a human hours, but AI can sift through the possibilities rapidly. AI Impacts Overall Business Performance Machines are getting smarter, and the ways society uses them to run businesses and households are changing daily. Using AI to measure the impact is the next step in the evolution of machine learning. Once you know how computers step in and take over the tasks that let your workers be more efficient, it’s easier to implement AI in the areas that will boost your company's growth.

How to Integrate AI Into Startup Operations for Enhanced Productivity

Stories, News & Mentions about AECOM

Aecom’s Stories on HackerNoon

Aecom's News & Mentions