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In a bold move that promises to reshape the landscape of artificial intelligence, President Donald Trump has unveiled the Stargate Initiative, a $500 billion project aimed at securing America's leadership in AI technology. Announced on January 22, 2025, this ambitious venture brings together tech giants OpenAI, SoftBank, and Oracle in a collaborative effort to build cutting-edge AI infrastructure across the United States. The Stargate Project: A New Era of AI Development The Stargate Project, spearheaded by OpenAI and SoftBank, plans to invest $500 billion over the next four years to construct state-of-the-art data centers and AI research facilities. With an initial deployment of $100 billion, the project is set to commence immediately, starting with a massive one-million square foot data center in Texas. <iframe class="ql-video" frameborder="0" allowfullscreen="true" src="https://www.youtube.com/embed/_GpvMIlVFMo?showinfo=0"></iframe> Key Players and Partnerships SoftBank CEO Masayoshi Son will serve as chairman of the Stargate Project, overseeing financial responsibilities, while OpenAI will manage operational aspects. The initiative also involves other tech powerhouses: - Oracle: Providing cloud computing and data center infrastructure expertise- NVIDIA: Contributing advanced GPU technology for AI computations- Microsoft: Continuing its partnership with OpenAI through Azure cloud services- Arm: Likely offering chip design capabilities Strategic Goals and Economic Impact The Stargate Initiative aims to achieve several key objectives: 1. Secure U.S. leadership in AI technology2. Create over 100,000 high-tech jobs across multiple states3. Foster clean energy innovation to power AI development4. Strengthen national security through advanced AI capabilities5. Stimulate economic growth and reindustrialize parts of the United States Technical Collaboration and Infrastructure The project will focus on developing a network of advanced data centers, leveraging Oracle's expertise in cloud computing. These facilities will house state-of-the-art hardware, including NVIDIA's latest GPU technologies, to support the demanding computational requirements of AI workloads. The infrastructure will incorporate: - Scalable data center designs- Energy-efficient cooling solutions- High-speed, low-latency network connectivity- Advanced cybersecurity protocols Implications for the Future The Stargate Initiative represents a significant step in the global AI race, positioning the United States to compete more effectively with countries like China. By investing heavily in domestic AI infrastructure, the U.S. aims to maintain its technological edge and protect national security interests. The project also has potential implications for various sectors, including healthcare, where AI advancements could accelerate medical research and improve patient care. Additionally, the initiative is expected to drive innovation in clean energy production, aligning with environmental sustainability goals. As the Stargate Project unfolds, it promises to usher in a new era of AI capabilities that could transform industries ranging from healthcare to national security. With its massive scale and collaborative approach, this initiative stands as a testament to the power of public-private partnerships in driving technological progress and economic growth. As the project develops, it will undoubtedly be watched closely by tech enthusiasts, policymakers, and global competitors alike, potentially reshaping the future of AI on a global scale.--Join the Future of Venture Capital Investing with NewnexNewnex is the platform focused on institutional investors where verified startups, VCs, and LPs converge for private fundraising and investment through trusted references. Centralize your fundraising and investment activities and access the global VC network with just a few clicks. Join for free at <a href="http://www.newnex.io/" rel="noopener noreferrer" target="_blank">www.newnex.io</a>&nbsp; We are digitalizing institutional investing to make VC as accessible as public markets while retaining the uniqueness of private markets. The mission is to unify 5,000+ VC/LP firms with 100,000 startups on a trusted platform for reference-only private deal-making.--Join the Future of Venture Capital Investing with NewnexNewnex is the platform focused on institutional investors where verified startups, VCs, and LPs converge for private fundraising and investment through trusted references. Centralize your fundraising and investment activities and access the global VC network with just a few clicks. Join for free at <a href="http://www.newnex.io/" rel="noopener noreferrer" target="_blank">www.newnex.io</a>&nbsp; We are digitalizing institutional investing to make VC as accessible as public markets while retaining the uniqueness of private markets. The mission is to unify 5,000+ VC/LP firms with 100,000 startups on a trusted platform for reference-only private deal-making.

The US Stargate Initiative: $500 Billion Leap into AI's Future

In a landmark decision just days before leaving office, President Joe Biden has introduced the AI Diffusion Rule, a comprehensive regulatory framework aimed at curbing the uncontrolled global spread of advanced artificial intelligence (AI) technologies. Announced on January 13, 2025, the policy represents one of the administration’s most significant efforts to safeguard national security while addressing the rapid proliferation of AI capabilities worldwide. What is the AI Diffusion Rule? The AI Diffusion Rule imposes strict export controls on cutting-edge AI technologies, including high-performance chips and proprietary AI model architectures. At its core, the framework categorizes nations into three tiers based on their geopolitical alignment and level of trust, dictating their access to U.S. AI technology. The Three-Tier System1.	Tier 1: Trusted AlliesCountries like NATO members, Japan, and Australia will experience minimal restrictions, enjoying relatively unfettered access to U.S. AI technologies.2.	Tier 2: Controlled AccessNations with intermediate relations will face stringent licensing requirements, restricting access to specific high-end AI technologies.3.	Tier 3: Restricted NationsAdversarial powers, including China and Russia, are subject to the tightest controls, effectively barring them from acquiring advanced AI-related exports. Key Components of the Rule•	Export Restrictions: Limits on the sale of advanced computing chips and closed AI model weights.•	Global Licensing System: A mechanism requiring nations and companies to obtain licenses for access to frontier AI technologies.•	Security Measures: Companies must implement robust physical and cybersecurity protocols to secure sensitive AI models.•	120-Day Grace Period: Allows stakeholders to adapt to the new requirements before enforcement begins.•	Compliance Requirements: Firms must demonstrate adherence to the rule to gain approval for exports. The Biden Administration’s Rationale The Biden administration has positioned the rule as essential for maintaining the United States’ edge in the global AI race. Commerce Secretary Gina Raimondo highlighted the dual objectives of safeguarding advanced AI technologies from adversaries and fostering responsible international AI development. The administration contends that unchecked diffusion of AI capabilities could jeopardize global security, economic stability, and democratic governance. A Balancing Act: Security vs. Innovation While emphasizing the necessity of the rule, the administration acknowledges the need for a collaborative international framework to prevent fragmentation of AI development. By partnering closely with allies, the U.S. hopes to establish a shared global standard for AI governance. Tech Industry Backlash Despite its lofty goals, the AI Diffusion Rule has sparked significant resistance from major tech companies and industry groups.•	Nvidia, a global leader in AI chips, criticized the policy as “misguided,” warning that it could stifle innovation, disrupt supply chains, and lead to economic slowdowns.•	The Information Technology Industry Council echoed concerns, cautioning against the risk of isolating the U.S. tech industry from global markets. Economic Risks Critics argue that the rule’s restrictive nature could:•	Undermine U.S. leadership in AI innovation by alienating key global markets.•	Accelerate competitors’ development of independent AI ecosystems.•	Trigger a global race to bypass restrictions, potentially reducing the effectiveness of export controls. A Political Turning Point The policy’s future is uncertain as the incoming Trump administration is set to reassess its viability. While the AI Diffusion Rule reflects the Biden administration’s assertive approach to tech regulation, its enforcement will depend on the priorities of the new administration. Balancing national security with economic competitiveness is expected to remain a key challenge. Global Implications The AI Diffusion Rule underscores the intensifying geopolitical competition over emerging technologies. With nations vying for dominance in AI, the framework seeks to:•	Establish U.S. leadership in regulating AI development.•	Foster international cooperation among trusted allies.•	Curtail adversarial nations’ access to transformative technologies. Potential Outcomes•	Strengthened Alliances: Enhanced collaboration among Tier 1 nations could solidify collective technological leadership.•	Technological Decoupling: Restrictive policies may accelerate the divide between Western and Eastern technology ecosystems.•	Global Innovation Bottleneck: Fragmentation of global AI development could slow overall progress in the field. The AI Diffusion Rule is a bold attempt by the President Biden administration to address the complex challenges posed by the global AI race. By instituting export controls and security protocols, the rule aims to shape the global AI landscape, ensuring responsible diffusion of advanced technologies. However, its long-term success will depend on industry adaptation, international cooperation, and the willingness of future administrations to strike a delicate balance between security and innovation. As the world watches this pivotal development, one thing is clear: the AI Diffusion Rule is set to redefine the contours of global AI regulation and technological competition for years to come.

AI Diffusion Rule: US's Move to Reshape the Global AI Landscape

The following framework provides a systematic approach for nation-states to evaluate their progress across the 20 pillars of AI leadership. Each pillar is associated with specific key performance indicators (KPIs), metrics, and targets to ensure comprehensive assessment and continuous improvement. 1. National AI Policy•	KPIs:•	AI as a percentage of GDP contribution.•	AI-specific government spending (absolute and % of national budget).•	Regulatory agility index (frequency and timeliness of AI-related policy updates). 2. Education and Talent Development•	KPIs:•	Percentage of workforce trained in AI-related skills.•	Number of AI graduates and postgraduates annually.•	Number of public-private partnerships for AI education. 3. Access to Data•	KPIs:•	Volume of data available in open data platforms.•	Percentage of businesses sharing anonymized data.•	Data privacy compliance rate. 4. Infrastructure•	KPIs:•	National compute power ranking (e.g., number of GPUs/TPUs per capita).•	Percentage of population with broadband access.•	Energy efficiency of national data centers (PUE - Power Usage Effectiveness). 5. AI Ecosystem•	KPIs:•	Number of AI startups established annually.•	Annual funding raised by AI startups.•	Collaboration score (measured by cross-sectoral and academic-industry partnerships). 6. Research and Niche Leadership•	KPIs:•	Number of AI patents filed annually.•	Global ranking in niche AI domains (e.g., AI in healthcare or energy).•	Percentage of GDP allocated to AI R&amp;D. 7. Ethical AI Development•	KPIs:•	Compliance rate with ethical AI guidelines.•	Public trust index in AI systems.•	Adoption rate of “ethics by design” frameworks in national AI projects. 8. Long-Term Funding•	KPIs:•	Total AI funding (government + private sector) as a percentage of GDP.•	Growth rate of venture capital in AI.•	Tax incentives claimed for AI R&amp;D. 9. Global Market Access•	KPIs:•	Export revenue from AI products and services.•	Number of international partnerships for AI.•	Adoption of national AI standards in global markets. 10. Emerging AI Trends•	KPIs:•	Investments in generative AI and quantum AI.•	Number of human-AI collaboration tools developed.•	Publications in top AI journals addressing emerging trends. 11. Multilateral Cooperation•	KPIs:•	Number of AI-focused MOUs signed with other nations.•	Participation rate in international AI standardization efforts.•	Funding allocated to joint global AI initiatives. 12. National Security•	KPIs:•	Investment in AI-powered defense systems.•	Number of AI-driven cybersecurity incidents neutralized.•	National preparedness index for malicious AI threats. 13. Societal Good•	KPIs:•	Number of public sector AI applications deployed.•	Reduction in healthcare costs due to AI interventions.•	Increase in crop yield through AI-driven agriculture solutions. 14. Sustainability and Green AI•	KPIs:•	Percentage of AI projects meeting green standards.•	Reduction in national carbon footprint through AI.•	Number of AI tools developed for climate change mitigation. 15. Inclusive AI Development•	KPIs:•	Representation of minorities in AI R&amp;D workforce.•	Accessibility of AI tools for underserved communities.•	Growth in AI solutions addressing disabilities. 16. AI-Ready Legal and Judicial Systems•	KPIs:•	Number of legal disputes resolved using AI.•	Frequency of AI training programs for legal professionals.•	Legal updates addressing AI technologies (e.g., biannual updates). 17. Metrics and Accountability•	KPIs:•	AI readiness index (published annually).•	Frequency and transparency of AI impact reports.•	Public engagement in AI policy discussions. 18. Global Branding and Soft Power•	KPIs:•	Global rankings in AI thought leadership.•	Number of international AI summits hosted.•	Media coverage of national AI achievements. 19. Private Sector Engagement•	KPIs:•	Number of public-private AI projects.•	Growth in corporate AI R&amp;D spending.•	Percentage of enterprises adopting AI solutions. 20. Speed and Innovation•	KPIs:•	Time-to-market for new AI solutions.•	Number of AI pilots launched annually.•	Growth rate of patents filed in cutting-edge AI domains. Implementation and Monitoring•	Scorecard System: Assign scores (1-10) for each KPI to create a composite AI leadership score.•	Quarterly Reviews: Monitor progress with a centralized AI task force.•	Global Benchmarking: Compare with other leading nations to identify gaps and opportunities. This framework ensures that nations track, measure, and continuously improve their AI strategies while maintaining focus on ethics, societal impact, and inclusivity.--Join the Future of Venture Capital Investing with NewnexNewnex is the platform focused on institutional investors where verified startups, VCs, and LPs converge for private fundraising and investment through trusted references. Centralize your fundraising and investment activities and access the global VC network with just a few clicks. Join for free at <a href="http://www.newnex.io/" rel="noopener noreferrer" target="_blank">www.newnex.io</a>&nbsp; We are digitalizing institutional investing to make VC as accessible as public markets while retaining the uniqueness of private markets. The mission is to unify 5,000+ VC/LP firms with 100,000 startups on a trusted platform for reference-only private deal-making. Disclaimer: The information presented in this article is based on available sources and may not be entirely accurate or up-to-date. We do not guarantee the accuracy of the content, and readers should conduct their own research and consult with financial professionals before making any decisions.

Measurement Framework for National AI Leadership

Artificial intelligence (AI) is a transformative force reshaping industries, societies, and global power structures. To lead the AI revolution, nations need a holistic strategy that addresses talent, infrastructure, data, ethics, and societal impact. This comprehensive blueprint outlines 20 pillars for establishing and maintaining global AI leadership. 1. Establish a National AI PolicyA robust AI policy sets the foundation for success, providing a roadmap for innovation and aligning resources.•	AI as a National Priority: Designate AI as a critical driver of economic and societal growth.•	Balanced Regulation: Encourage innovation while addressing ethical concerns like privacy and safety.•	Sovereign AI Capabilities: Invest in domestic tools to reduce reliance on foreign technologies and protect national security.•	Government Funding: Allocate significant resources to research, public-private partnerships, and startups. 2. Invest in Education and Talent DevelopmentTalent is the bedrock of AI innovation. Building a skilled workforce ensures competitiveness.•	Early AI Education: Introduce coding and AI literacy in school curriculums.•	University Programs: Expand graduate and postgraduate AI degree offerings.•	Reskilling Initiatives: Provide accessible programs to upskill workers in automated industries.•	Global Talent Attraction: Offer incentives and streamlined immigration pathways for top AI experts.•	Public Awareness Campaigns: Educate the public on AI’s potential benefits and risks. 3. Ensure Access to DataData fuels AI innovation. Nations must secure diverse, high-quality datasets while ensuring privacy and security.•	Open Data Platforms: Establish repositories of anonymized, non-sensitive data for researchers and businesses.•	Public-Private Collaboration: Encourage data sharing among companies and research institutions.•	Data Sovereignty: Implement policies to control and secure critical national data.•	Data Collection Infrastructure: Expand IoT networks and leverage synthetic data generation.•	Global Data Partnerships: Partner internationally to access diverse datasets, respecting privacy laws. 4. Build Robust InfrastructureAI development demands cutting-edge infrastructure for scalability and deployment.•	Compute Power: Invest in high-performance computing, including GPUs, TPUs, and quantum computing.•	Cloud and Edge Computing: Develop scalable infrastructure for real-time AI applications.•	Broadband Access: Ensure nationwide high-speed internet for equitable AI adoption.•	Energy Efficiency: Prioritize sustainable, energy-efficient computing solutions. 5. Foster a Thriving AI EcosystemAn interconnected ecosystem accelerates AI innovation and commercialization.•	Innovation Hubs: Establish AI-focused hubs to connect academia, enterprises, and startups.•	Startup Support: Provide funding, mentorship, and market access for AI startups.•	Cross-Sector Collaboration: Foster collaboration across industries like healthcare, agriculture, and energy.•	AI Export Strategy: Position AI solutions as key exports in areas of national expertise. 6. Specialize in Research and Niche LeadershipSpecialization helps nations excel in sectors where they have a competitive advantage.•	Industry-Specific AI: Focus on AI applications for healthcare, climate change, and advanced manufacturing.•	Funding R&amp;D: Increase funding for fundamental breakthroughs and applied research.•	International Collaboration: Share knowledge and resources with global research institutions. 7. Prioritize Ethical AI DevelopmentTrust and fairness are crucial for sustainable AI leadership.•	Ethics by Design: Integrate fairness, transparency, and safety into AI systems from the outset.•	Regulatory Alignment: Lead global discussions on ethical AI standards.•	Inclusivity: Ensure that AI benefits marginalized and underserved communities.•	Public Trust: Maintain open dialogue to address fears around data misuse and job displacement. 8. Secure Long-Term FundingConsistent funding is essential to stay competitive in the global AI race.•	Government Grants: Provide substantial funding for research and innovation.•	Venture Capital Ecosystem: Attract private investors with favorable policies.•	R&amp;D Tax Credits: Offer incentives for companies investing in AI research. 9. Accelerate Global Market AccessGlobal markets are key to scaling AI solutions.•	Trade Partnerships: Leverage agreements to expand AI offerings internationally.•	Localization: Adapt AI solutions for different cultural and regulatory environments.•	Standards Leadership: Influence global AI standards to align with national priorities. 10. Adapt to Emerging AI TrendsStaying ahead of trends ensures sustained leadership.•	Generative AI: Invest in cutting-edge tools while addressing risks like misinformation.•	Quantum AI: Prepare for the convergence of AI and quantum computing.•	Human-AI Collaboration: Focus on augmenting human capabilities alongside automation. 11. Promote Multilateral CooperationGlobal challenges require collaborative solutions.•	Shared AI Initiatives: Partner on AI-driven solutions for climate change and health crises.•	Standardization: Work with international bodies to set safety and ethical standards.•	Education Partnerships: Promote global AI education through joint research and programs. 12. Strengthen National SecurityAI has transformative implications for defense and security.•	AI-Powered Defense: Develop autonomous systems for surveillance and cybersecurity.•	Counter-AI Strategies: Prepare for and neutralize malicious AI use by adversaries.•	AI in Diplomacy: Use AI for geopolitical analysis and strategic decision-making. 13. Leverage AI for Societal GoodAI leadership should prioritize societal benefits.•	Public Services: Enhance healthcare, education, and safety through AI.•	Climate Solutions: Develop AI tools for renewable energy and environmental conservation.•	Equitable Benefits: Reduce inequalities and improve quality of life for all citizens. 14. Prioritize Sustainability and Green AIAI must align with environmental goals.•	Energy Efficiency: Promote energy-efficient AI systems and algorithms.•	AI for Sustainability: Use AI for precision agriculture and environmental monitoring.•	Green AI Policies: Require sustainability assessments for AI projects. 15. Focus on Inclusive AI DevelopmentAI should reflect the diversity of its users.•	Diverse Workforce: Encourage diversity in AI research and development teams.•	Localized Solutions: Create AI tailored to rural and underserved communities.•	Accessibility: Invest in AI tools for differently-abled individuals. 16. Establish AI-Ready Legal and Judicial SystemsAI’s rapid evolution demands adaptable legal frameworks.•	Judicial Training: Equip judges and regulators with AI literacy.•	AI Dispute Resolution: Develop tools for resolving legal disputes involving AI.•	Proactive Legislation: Regularly update laws for emerging AI domains. 17. Develop Metrics and AccountabilityMeasuring progress ensures sustained success.•	AI Readiness Index: Track progress in infrastructure, ethics, and innovation.•	Impact Assessment: Audit AI’s societal and economic contributions.•	Transparent Reporting: Share milestones with citizens to foster trust. 18. Strengthen Global Branding and Soft PowerA strong national identity in AI enhances influence.•	Cultural AI Export: Promote AI solutions that reflect national values.•	Thought Leadership: Host forums and summits to shape global AI conversations.•	AI Diplomacy: Use AI achievements to enhance international relations. 19. Engage the Private SectorPrivate companies drive much of AI innovation.•	Corporate AI Governance: Encourage ethical practices in businesses.•	Public-Private Challenges: Host competitions to solve public problems with private expertise.•	Industry Solutions: Co-develop AI applications for finance, healthcare, and logistics. 20. Compete on Speed and InnovationAgility and adaptability are key to outpacing competitors.•	Rapid Iteration: Foster a culture of experimentation and deployment.•	First-Mover Advantage: Enter emerging sectors early to establish leadership.•	Continuous Innovation: Embrace a mindset of constant improvement. Nations that prioritize these 20 pillars - talent, infrastructure, ethics, collaboration, and societal impact—will lead the AI revolution and shape the future of humanity. Success demands not only technological innovation but also inclusivity, agility, and trust. --Join the Future of Venture Capital Investing with NewnexNewnex is the platform focused on institutional investors where verified startups, VCs, and LPs converge for private fundraising and investment through trusted references. Centralize your fundraising and investment activities and access the global VC network with just a few clicks. Join for free at <a href="http://www.newnex.io/" rel="noopener noreferrer" target="_blank">www.newnex.io</a>&nbsp; We are digitalizing institutional investing to make VC as accessible as public markets while retaining the uniqueness of private markets. The mission is to unify 5,000+ VC/LP firms with 100,000 startups on a trusted platform for reference-only private deal-making. Disclaimer: The information presented in this article is based on available sources and may not be entirely accurate or up-to-date. We do not guarantee the accuracy of the content, and readers should conduct their own research and consult with financial professionals before making any decisions.

The Blueprint for AI Leadership: Strategies for Competing in the Global AI Race

OpenAI has taken a bold step in making artificial intelligence more accessible by integrating ChatGPT with WhatsApp and launching a phone service. This move brings the popular AI chatbot to billions of users through familiar communication channels. WhatsApp users can now chat with ChatGPT by simply adding a designated phone number to their contacts. To get started, open WhatsApp, add a new contact with the number +1 800-242-8478 (which spells out 800-CHATGPT). Save the contact as "ChatGPT" or any preferred name, and you're ready to start a conversation. For those in the United States, OpenAI has introduced a toll-free number (1-800-ChatGPT) that allows voice conversations with the AI assistant. This service offers 15 minutes of free interaction per month for anyone dialing from a US number, making AI engagement as simple as making a phone call. While the WhatsApp version comes with some limitations - it only supports text conversations, has a knowledge cutoff date of September 2021, and can't be added to group chats - it provides a straightforward way for users to experience AI without needing to create an OpenAI account. To use ChatGPT on WhatsApp effectively, keep your messages clear and concise for better responses. You can ask follow-up questions or request clarifications in the same chat thread. Remember that there may be daily message limits, although the service is free to use. This expansion is part of OpenAI's broader strategy to reduce barriers to AI adoption and showcase its potential to a wider audience. By leveraging familiar platforms like WhatsApp and traditional phone calls, OpenAI aims to make AI technology more approachable and less intimidating to the average user. As AI continues to evolve and integrate into our daily lives, initiatives like this play a crucial role in democratizing access to advanced technologies. While the current offering is described as experimental, it represents a significant step towards making AI a more common and accessible tool for people around the world.---Join the Future of Venture Capital Investing with Newnex <a href="https://www.newnex.io/edit/blogs/www.newnex.io" rel="noopener noreferrer" target="_blank">Newnex</a> is redefining venture capital by fostering collaborative and private investing and fundraising between VCs (GPs), Limited Partners (LPs), and Startups. Newnex simplifies syndication and co-investment for institutional investors, with a mission to connect 5,000+ VC and LP firms and 100,000 venture scale startups on a trusted platform for seamless, reference-only private deal-making. Join Newnex for free <a href="http://www.newnex.io/" rel="noopener noreferrer" target="_blank">www.newnex.io</a>

ChatGPT comes to WhatsApp and Phone calls - Add +1 1800 242 8478 to your contacts

Nvidia has unveiled its latest offering in the world of compact AI computing: the Jetson Orin Nano Super Developer Kit. This palm-sized supercomputer, priced at an accessible $249, is set to revolutionize the landscape of AI development for hobbyists, students, and small businesses. Specifications and Performance The Jetson Orin Nano Super boasts impressive specifications that punch well above its weight class. It delivers up to 67 INT8 TOPS (Trillion Operations Per Second) of AI performance, marking a 70% increase over its predecessor. The device also features a 50% boost in memory bandwidth, reaching 102GB/s. These improvements translate to a 1.7x leap in generative AI inference performance compared to the previous model. At the heart of the Jetson Orin Nano Super is a system-on-module (SoM) featuring an NVIDIA Ampere architecture GPU with tensor cores and a 6-core Arm Cortex-A78AE CPU. This powerful combination allows for multiple concurrent AI application pipelines and high-performance inference. The device supports up to four cameras, offering higher resolution and frame rates than earlier versions. <iframe class="ql-video" frameborder="0" allowfullscreen="true" src="https://www.youtube.com/embed/S9L2WGf1KrM?showinfo=0"></iframe> Use Cases and Applications The Jetson Orin Nano Super is designed to handle a wide array of AI tasks locally. It's particularly well-suited for: 1. Running large language models (LLMs) and creating chatbots2. Building visual AI agents3. Deploying AI-powered robots4. Developing smart surveillance systems5. Creating AI-enhanced smart home devices and wearables6. Advancing autonomous vehicle technology7. Facilitating research and education in AI Its versatility makes it an ideal platform for those looking to develop skills in generative AI, robotics, or computer vision. Configuration and Software Ecosystem The Jetson Orin Nano Super comes with NVIDIA's comprehensive AI software stack, including popular frameworks and tools. It supports CUDA, CuDNN, and TensorRT, allowing developers to create sophisticated AI applications. The device runs on Linux, providing a familiar environment for many developers. NVIDIA also offers the Isaac platform for robotics and Metropolis for vision AI, expanding the potential applications of the Jetson Orin Nano Super. The company has emphasized the device's ability to handle foundation models, reflecting the AI industry's shift towards more generalized, multi-purpose AI systems. Competitors and Market Position While the Jetson Orin Nano Super stands out in its price-to-performance ratio, it does face competition in the compact AI computing space. Devices like the Radxa Fogwise Airbox and Firefly AIO-1684XQ motherboard offer similar capabilities for edge AI applications. However, NVIDIA's strong software ecosystem, extensive developer community, and competitive pricing give the Jetson Orin Nano Super a significant edge. The introduction of this affordable, high-performance AI computer could spark a new wave of innovation in AI development, much like how the Raspberry Pi revolutionized DIY computing projects. By lowering the barriers to entry for advanced AI tools, NVIDIA is positioning itself at the forefront of democratizing AI technology. As AI continues to permeate various aspects of technology and daily life, the Jetson Orin Nano Super Developer Kit represents a significant step towards making powerful AI capabilities accessible to a broader audience. Whether for hobbyist projects, educational purposes, or small-scale commercial applications, this palm-sized supercomputer opens up new possibilities in the realm of AI development and deployment.--Join the Future of Venture Capital Investing with Newnex <a href="https://www.newnex.io/edit/blogs/www.newnex.io" rel="noopener noreferrer" target="_blank">Newnex</a> is redefining venture capital by fostering collaborative and private investing and fundraising between VCs (GPs), Limited Partners (LPs), and Startups. Newnex simplifies syndication and co-investment for institutional investors, with a mission to connect 5,000+ VC and LP firms and 100,000 venture scale startups on a trusted platform for seamless, reference-only private deal-making. Join Newnex for free <a href="http://www.newnex.io/" rel="noopener noreferrer" target="_blank">www.newnex.io</a>

NVIDIA's Jetson $249 Orin Nano Super: Revolutionizing Edge AI for Developers and Everyday Users

Uber, the tech giant known for revolutionizing transportation, is making waves in the artificial intelligence industry with its new division, Scaled Solutions. This innovative venture transforms Uber's internal data labeling team into a powerhouse serving both in-house needs and external clients, marking a significant leap into the AI services market. Scaled Solutions: A Game-Changer in AI Data AnnotationUber's Scaled Solutions is rapidly emerging as a formidable player in the AI data labeling arena. With a global workforce spanning the United States, Canada, India, Poland, and Nicaragua, this division offers a comprehensive suite of services including:Image and video annotation<ul><li>Text labeling</li><li>Map validation</li><li>AI-generated code evaluation</li></ul> The team's expertise stems from Uber's vast experience in managing gig economy workers, giving them a unique edge in the market. High-Profile Partnerships and Market ImpactScaled Solutions has already caught the attention of industry leaders. Partnerships with Aurora Innovation, a self-driving vehicle company, and Niantic, the creator of Pokémon Go, showcase the division's capabilities and market appeal. These collaborations not only validate Uber's approach but also position the company as a serious contender in the AI services sector. Competing in a Growing MarketThe launch of Scaled Solutions puts Uber in direct competition with established players like Scale AI and challenges traditional BPO providers such as TaskUs and Telus International. Uber's entry is poised to disrupt the market dynamics, leveraging its unique position at the intersection of gig economy management and AI technology. Strategic Advantages of Scaled SolutionsBy separating Scaled Solutions from its core business, Uber gains several strategic advantages:1. Revenue Diversification: Expanding beyond ride-hailing and delivery services.<ol><li>Expertise Utilization: Applying gig economy management skills to a new, high-growth sector.</li><li>Market Expansion: Tapping into the rapidly growing AI data labeling market.</li><li>Specialized Development: Creating tools and processes tailored for AI data annotation.</li><li>External Client Focus: Effectively marketing and providing services to a broader client base.</li></ol> The Future of AI ServicesUber's bold move into AI data labeling through Scaled Solutions represents a significant shift in the company's strategy. It positions Uber not just as a transportation and delivery company, but as a potential leader in AI services. As the demand for high-quality data annotation continues to grow in the AI industry, Uber's Scaled Solutions is well-positioned to play a crucial role in shaping the future of artificial intelligence development. ﻿This strategic expansion showcases Uber's adaptability and foresight, potentially transforming the company into a major player in the AI services industry while maintaining its stronghold in the transportation sector. As Scaled Solutions continues to evolve and attract more high-profile clients, it may well become a cornerstone of Uber's future growth and innovation strategy. ---Join the Future of Venture Investing with Newnex<a href="https://www.newnex.io/edit/blogs/www.newnex.io" rel="noopener noreferrer" target="_blank">Newnex</a> is redefining venture capital by fostering seamless collaboration between General Partners (GPs), Limited Partners (LPs), and startups. Designed for institutional investors, our platform streamlines syndication and co-investment across both direct and LP deals. With a mission to unite over 5,000 VC and LP firms on a single, unified platform, Newnex enables effortless private deal-making based on reference-only transactions.

Uber Revolutionizes AI Data Labeling with Scaled Solutions

Large Language Models (LLMs) have revolutionized natural language processing, offering impressive capabilities in text generation, translation, and various other linguistic tasks. While proprietary models like GPT-3 and GPT-4 have garnered significant attention, open source LLMs have emerged as powerful alternatives, providing accessibility, transparency, and flexibility to researchers and developers worldwide. Understanding LLMsLarge Language Models are artificial intelligence systems trained on vast amounts of text data to understand and generate human-like text. These models use deep learning techniques, particularly transformer architectures, to process and generate language. LLMs can perform a wide range of tasks, from answering questions and writing content to assisting with code generation and language translation. The Rise of Open Source LLMs Open source LLMs have gained popularity due to several advantages:1. Transparency: Users can inspect the code and understand the model's architecture and training methodology.2. Customization: Developers can fine-tune these models for specific use cases or domains.3. Cost-effectiveness: While initial setup costs may be significant, open source LLMs often prove more economical in the long run compared to proprietary alternatives.4. Community support: A vibrant ecosystem of developers contributes to the improvement and maintenance of these models. Notable Open Source LLMs Here's a list of some prominent open source Large Language Models: 1. LLaMA 2: Developed by Meta, LLaMA 2 comes in 7B, 13B, and 70B parameter versions, offering scalability and performance comparable to proprietary models 2. Mistral 7B: Created by Mistral AI, this model outperforms many larger models despite its relatively small size 3. Falcon: Available in 7B, 40B, and 180B parameter versions, Falcon is known for its excellent performance and multilingual capabilities 4. BLOOM: With 176 billion parameters, BLOOM is a multilingual model that supports 46 languages and 13 programming languages 5. GPT-NeoX-20B: Developed by EleutherAI, this model is architecturally similar to GPT-3 and is suitable for advanced content generation tasks 6. MPT: MosaicML's MPT comes in 7B and 30B parameter versions, offering efficiency improvements and commercial usage rights 7. BERT: One of the earliest transformer-based models, BERT remains widely used for various NLP tasks and has spawned numerous variants 8. GPT-J: Another EleutherAI creation, GPT-J is a 6B parameter model that offers good performance for its size 9. Dolly 2.0: Developed by Databricks, Dolly 2.0 is a fine-tuned version of GPT-J, demonstrating the potential of smaller models with targeted training 10. XGen-7B: Salesforce's entry into the open source LLM space, XGen-7B focuses on handling longer context windows efficiently 11. Mixtral 8x7B: A cutting-edge sparse mixture-of-experts model that offers impressive performance across various tasks These open source LLMs cater to different needs, from research and experimentation to commercial applications. Their availability has democratized access to advanced language AI, fostering innovation and pushing the boundaries of what's possible in natural language processing. As the field of AI continues to evolve rapidly, open source LLMs are likely to play an increasingly important role, offering alternatives to proprietary models and driving progress in language understanding and generation technologies.

Open Source Large Language Models: An Overview

In the rapidly evolving landscape of artificial intelligence, particularly with the rise of generative AI, organizations are increasingly turning to AI guardrails to ensure their AI systems operate safely, ethically, and in alignment with company values. Much like guardrails on highways protect vehicles from veering off course, AI guardrails are designed to prevent AI systems from producing harmful, inaccurate, or inappropriate content. These guardrails serve multiple crucial functions. They help maintain privacy and security by protecting against malicious attacks that could manipulate AI-generated outcomes. They also ensure regulatory compliance, which is particularly important as government scrutiny of AI intensifies. Perhaps most importantly, AI guardrails help build and maintain trust with customers and the public by continuously monitoring and reviewing AI-generated outputs. There are several types of AI guardrails, each addressing specific risks:1. Appropriateness guardrails filter out toxic, harmful, or biased content.2. Hallucination guardrails prevent the generation of factually incorrect or misleading information.3. Regulatory-compliance guardrails ensure adherence to relevant laws and standards.4. Alignment guardrails keep generated content in line with user expectations and brand consistency.5. Validation guardrails check that content meets specific criteria. AI guardrails typically consist of four main components: a checker that scans for issues, a corrector that refines and improves outputs, a rail that manages the interaction between the checker and corrector, and a guard that oversees the entire process. Implementing AI guardrails at scale requires a multidisciplinary approach. Organizations should design guardrails with input from diverse stakeholders, define clear content quality metrics, and adopt a modular approach for easy integration and scalability. It's also crucial to develop new capabilities and roles within the organization to manage these systems effectively. While AI guardrails don't guarantee completely risk-free AI systems, they are a critical tool in creating a safer environment for AI innovation and transformation. As AI continues to advance, we can expect to see not only new types of AI systems but also evolving standards for their development and operation, with guardrails playing a central role in responsible AI implementation.

AI Guardrails: Ensuring Responsible AI Implementation

The European Union's Artificial Intelligence Act (AI Act) is a comprehensive regulation designed to ensure the ethical and safe development and use of AI technologies across the EU. The AI Act is now published by the EU. Here is a summary of its key points and practical information: Objectives and Scope<ol><li>Ensuring Trustworthy AI: The primary goal of the AI Act is to foster the development and use of AI systems that are safe, transparent, and respectful of fundamental rights. It aims to create a regulatory framework that balances innovation with the protection of public interests and fundamental rights.</li><li>Risk-Based Approach: The AI Act categorizes AI systems into different risk levels:</li></ol><ul><li class="ql-indent-1">Unacceptable Risk: Practices that pose a clear threat to safety, livelihoods, and rights are banned. These include social scoring by governments and certain uses of real-time biometric identification.</li><li class="ql-indent-1">High Risk: AI systems that significantly impact people's lives (e.g., those used in critical infrastructure, employment, and law enforcement) are subject to strict requirements. These include robust risk management systems, high-quality data sets, and detailed documentation.</li><li class="ql-indent-1">Limited and Minimal Risk: These AI systems have fewer requirements but must still adhere to transparency obligations, such as informing users they are interacting with AI.</li></ul> <ol><li>Conformity Assessments: High-risk AI systems must undergo rigorous conformity assessments before being marketed. This ensures they meet the necessary standards for safety and performance.</li><li>National Authorities and European Artificial Intelligence Board: Each EU member state will appoint national authorities to oversee the implementation and enforcement of the AI Act. The European Artificial Intelligence Board will coordinate these efforts to ensure consistency across the EU.</li></ol>Supporting Innovation<ol><li>Regulatory Sandboxes: To encourage innovation, the AI Act includes provisions for regulatory sandboxes, allowing developers to test AI systems in a controlled environment under regulatory supervision.</li><li>Support for SMEs: Recognizing the challenges faced by small and medium-sized enterprises (SMEs), the AI Act provides measures to support their compliance, such as reduced fees for conformity assessments.</li></ol> Fundamental Rights and Ethical Considerations<ol><li>Protection of Fundamental Rights: The AI Act is designed to safeguard fundamental rights, including privacy, non-discrimination, and the right to a fair trial. It ensures that AI systems are developed and used in ways that do not infringe on these rights.</li><li>Ethical AI Development: The Act promotes the development of AI technologies that contribute positively to society and the environment. It encourages the use of AI to enhance human well-being and societal good.</li></ol> Practical Implications<ol><li>Compliance Costs: For businesses and public authorities developing or using high-risk AI systems, compliance costs are estimated between €6,000 and €7,000 per system, with additional annual costs for human oversight ranging from €5,000 to €8,000. Verification costs could add another €3,000 to €7,500.</li><li>Transparency and Accountability: AI systems interacting with humans, such as chatbots, must clearly inform users they are interacting with AI. Systems generating deep fakes must disclose their artificial nature.</li></ol> Legal Basis and Harmonization<ol><li>Legal Framework: The AI Act is based on Article 114 of the Treaty on the Functioning of the European Union (TFEU), ensuring the establishment and functioning of the internal market by harmonizing rules for AI systems.</li><li>Avoiding Fragmentation: By setting harmonized rules, the AI Act aims to prevent the fragmentation of the internal market, ensuring legal certainty and a level playing field for AI developers and users across the EU.</li></ol> The AI Act sets a global standard for AI governance, promoting innovation while safeguarding ethical standards and public trust. It ensures that AI technologies are developed and used in ways that are safe, transparent, and respectful of fundamental rights, fostering a trustworthy AI ecosystem within the EU. Visit the official document on <a href="https://eur-lex.europa.eu/legal-content/EN/TXT/HTML/?uri=OJ:L_202401689" rel="noopener noreferrer" target="_blank">EUR-Lex</a><a href="https://www.deloitte.com/lu/en/Industries/investment-management/perspectives/eu-ai-act-is-finally-here-requirements-overview.html" rel="noopener noreferrer" target="_blank">Deloitte summary</a> #ArtificialIntelligence #EU #AI #Regulation

EU's AI Act Explained 

18 December This week has not been carrying too many block buster events, nonetheless there are some important news you need to be informed about. Newnex is bringing the AI top-news and discussions on AI happening every week. Here is last week's top developments. <ol><li>The UK high court rules that AI invention is patentable. Previously UK IPO had refused to recognise AI patent considering it to be a computer program. <a href="https://www.osborneclarke.com/insights/uk-high-court-finds-ai-invention-patentable#:~:text=In%20a%20positive%20move%20for,and%20therefore%20was%20not%20patentable." rel="noopener noreferrer" target="_blank">Read more</a> and <a href="https://www.juve-patent.com/cases/uk-ipo-suspended-its-guidelines-on-ai-patents-after-high-court-judgment/#:~:text=The%20UK%20High%20Court%20handed,its%20guidelines%20on%20AI%20patents.&amp;text=Experts%20around%20the%20world%20have,AI%20inventions%20can%20be%20patented." rel="noopener noreferrer" target="_blank">Read other news</a> (did not happen last week but important)</li></ol> The gist:The High Court has overturned a UK Intellectual Property Office (UKIPO) decision, ruling that an AI invention for media-file recommendations based on artificial neural networks (ANNs) is patentable. The judge found the invention did not fall within the computer program patentability exclusion, signaling a positive move for AI innovators. The decision is the first to consider the exclusion in the context of AI, potentially opening the door to patent protection for many AI inventions. The UKIPO has temporarily suspended its examination guidelines on AI-related patent applications while reviewing the judgment, highlighting the decision's significant impact on patent protection for AI in the UK. The ruling positions the UK as an AI-friendly jurisdiction and aligns with the government's push for AI development and innovation. 	2. EU's AI act is moving ahead - <a href="https://www.insideprivacy.com/artificial-intelligence/eu-artificial-intelligence-act-nearing-the-finish-line/" rel="noopener noreferrer" target="_blank">Read here</a> 	The gist:The European Parliament, Council of the European Union, and European Commission have reached a political agreement on the EU Artificial Intelligence Act (AI Act) on December 9, 2023. The agreement covers key aspects, including the scope of the AI Act, classification of AI systems as "high-risk," and law enforcement exemptions. The AI Act aims to regulate the development, import, deployment, and use of AI systems in the EU. The agreement includes prohibitions on certain AI practices, obligations for high-risk AI systems, the right for citizens to lodge complaints, rules for general-purpose AI models, the establishment of a European AI Office and AI Board for oversight, and sanctions for non-compliance. The AI Act is expected to enter into force 20 days after publication in the EU Official Journal, with organizations required to comply two years after its entry into force. During the transitional period, the Commission will launch an AI Pact for developers to voluntarily commit to key obligations outlined in the Act. 	3. SEC probes investment advisors use of AI - <a href="https://www.wsj.com/articles/sec-probes-investment-advisers-use-of-ai-48485279" rel="noopener noreferrer" target="_blank">Read more</a> 	The gist:	The U.S. Securities and Exchange Commission (SEC) is conducting a targeted 				examination, or "sweep," to gather information from investment advisers on their use and oversight of artificial intelligence (AI). The SEC's examinations division has sent requests for information to multiple investment advisers, seeking details on AI-related marketing documents, algorithmic models for managing client portfolios, third-party providers, and compliance training. While the SEC's scrutiny does not imply suspicion of misconduct, it aligns with SEC Chairman Gary Gensler's expressed skepticism about the potential risks associated with the financial industry's increasing reliance on AI. The examination is part of the SEC's broader rule-making agenda, which includes proposed rules around the use of data analytics, including AI, with a focus on addressing conflicts of interest. The sweep targets specific concerns such as managing AI-related conflicts of interest, contingency plans for system failure, and the impact of AI systems on regulatory or legal issues. Despite ongoing evaluations of AI policies by many firms, the SEC's examination faces challenges due to the widespread adoption of AI technologies in the industry. 	4. SEC faces fierce pushback on plan to police AI investment advice - <a href="https://on.ft.com/472aHHV" rel="noopener noreferrer" target="_blank">Read </a>	<a href="https://on.ft.com/472aHHV" rel="noopener noreferrer" target="_blank">more</a> 	The gist:	Brokers, hedge funds, and investment advisers are strongly opposing the Securities and Exchange Commission's (SEC) proposed rules on the use of artificial intelligence (AI) in providing financial advice to investors. The SEC's July proposals, known as "Reg PDA," aim to eliminate conflicts of interest involving technology when advising clients. Critics argue that existing rules on investor protection are sufficient and that the SEC's definition of "technology" is too broad. Industry groups, including Sifma and the Investment Company Institute, have called for the withdrawal of Reg PDA, citing concerns about arbitrary rulemaking. The SEC, under Chair Gary Gensler, has faced significant opposition, and critics argue that the cumulative effect of numerous rule changes is straining the industry. Consumer groups support Reg PDA, emphasizing the need for stronger investor protections in the rapidly evolving landscape of AI-driven financial advice. Other news: - Swiss to use artificial intelligence post tests for passenger counting<a href="https://www.flightglobal.com/airlines/swiss-to-adopt-artificial-intelligence-passenger-counting-next-year-following-tests/156222.article" rel="noopener noreferrer" target="_blank">Read more</a> - Agencies Have Begun Implementation but Need to Complete Key requirements <a href="https://www.gao.gov/products/gao-24-105980" rel="noopener noreferrer" target="_blank">Read more</a> - EU policymakers reached a political agreement on Thursday (14 December) on legislation to bring the bloc’s product liability regime in line with technological developments, notably covering digital products like software, which includes Artificial Intelligence. <a href="https://www.euractiv.com/section/digital/news/eu-updates-product-liability-regime-to-include-software-artificial-intelligence/" rel="noopener noreferrer" target="_blank" style="color: rgb(51, 51, 51);">Read more</a> -- Join Newnex - scale your VC fund, direct and co-investments <a href="http://www.newnex.io/" rel="noopener noreferrer" target="_blank">www.newnex.io</a>

Last week in Artificial Intelligence (AI) 

BlackRock just published 2024 Private Markets Outlook. The Newnex team has parsed the key-takeaways from the report. There is a rapidly growing perception that the next decade of value creation is happening in private markets. We've seen reports including Family Offices pushing into private investments despite the good performing public equity. This timely report throws some more light into how private markets are expected to evolve in the coming years. Long-story short, private markets are set to soar. AI will be a game-changer. To begin with, there is no one-type of "private asset". Investors have to choose among the available assets to choose what's best for them. Private markets for the purpose of this report is a) Private Equity b) Private debt c) Infrastructure d) Real Estate. Our focus below is on PE. The Key take-aways for Private Markets with a focus on PE:<ol><li>Broad shifts in the economy and financial markets are positioning private markets to grow.</li><li>What are those broad shifts?</li><li class="ql-indent-1">Tightening lending standards resulting in banks reducing lending. Boom time for private debt and increasing reliability on equity financing.</li><li class="ql-indent-1">Companies are staying private longer, requiring a prominent place for private financing. Faster and flexible financing will drive growth.</li><li class="ql-indent-1">Fundraising in 2023 have been subdued, and as a result, less capital chasing investments. Hence more selective investments and good vintages.</li><li>Mega forces that are reshaping the world are:</li><li class="ql-indent-1">digital disruption and AI (private equity)</li><li class="ql-indent-1">the low-carbon transition (Infrastructure)</li><li class="ql-indent-1">the future of finance (private debt)</li><li class="ql-indent-1">demographic divergence (real estate)</li><li class="ql-indent-1">geographical fragmentation</li><li>Dry-powder, Capital calls and Distributions</li><li class="ql-indent-1">Private markets dry-powder set to touch $4tn, with the mega share with private equity ($2.5 tn).</li><li class="ql-indent-1">Capital calls increasing and outpacing distributions</li><li>Private Equity</li><li class="ql-indent-1">Rising interest rate, inflationary pressure, geopolitical and economic uncertainty, and correction in public markets drove slower PE activity.</li><li class="ql-indent-1">Valuations have declined from 11.9x EBITDA (2022) to 11.2x EBITDA (2023)</li><li class="ql-indent-1">Public-to-private transactions increased to 21% of deal value (compared to 15% the last 5 years)</li><li class="ql-indent-1">Less availability of debt has increased equity contributions in deal making</li><li class="ql-indent-1">Quality assets attract investments (industry leading companies, stable cash flow and return on capital)</li><li class="ql-indent-1">Good time to buy: Shortage of exit opportunities have left 75% of companies net cash-flow negative. Great secondary opportunity because (a) Sellers are motivated (b) Debt is hard to come by (c) innovative deal structuring including minority sales (d) corporate divestitures (e) moderated valuations</li></ol> BlackRock identifies that Artificial Intelligence will be a mega force having a horizontal and profound across industries. <a href="https://d1e00ek4ebabms.cloudfront.net/production/uploaded-files/2024-private-markets-outlook-stamped-69c37efb-c1de-4ffc-a214-646f5013ac32.pdf" rel="noopener noreferrer" target="_blank">Access the Full Report here</a>-------Join Newnex and scale venture capital investing. Consolidate LP, Direct and Co-investments in one place with <a href="http://www.newnex.io" rel="noopener noreferrer" target="_blank">www.newnex.io</a>

$4tn dry powder and key-takeaways for PE from Blackrock's 2024 Private Markets Outlook

Artificial Intelligence is scaling to have one of the most profound impacts on humanity. We are starting a new series to track AI developments every week. Our series will provide a snapshot on the main events of this past week in AI: AI news: <ul><li>Google launched Gemini, its long-awaited answer to ChatGPT - <a href="https://www.wired.com/story/google-gemini-ai-model-chatgpt/" rel="noopener noreferrer" target="_blank">Read more</a></li><li class="ql-indent-1">Google has already admitted at least one demo wasn't real - <a href="https://www.theverge.com/2023/12/7/23992737/google-gemini-misrepresentation-ai-accusation" rel="noopener noreferrer" target="_blank">Read here</a></li></ul> <ul><li>EU agrees landmark rules on regulating AI - <a href="https://www.newnex.io/blogs/artificial-intelligence/51" rel="noopener noreferrer" target="_blank">Read more</a></li></ul> <ul><li>French AI startup Mistral AI raises €400m funding and reaches €2bn valuation in 8-months. New joinees include Nvidia, A16z - <a href="https://www.pymnts.com/news/artificial-intelligence/2023/mistral-ai-raises-487-million-in-round-led-by-andreessen-horowitz/" rel="noopener noreferrer" target="_blank">Read more</a></li></ul> <ul><li>AMD launched AMD MI300x chip, its most advanced AI accelerator in the industry. AMD claims its product outperformed Nvidia's H100s. Nvidia is working on H200 but the market potential is huge for AMD to have a good play. <a href="https://www.crn.com/news/components-peripherals/amd-launches-instinct-mi300-ai-chips-to-challenge-nvidia-with-backing-from-microsoft-dell-and-hpe" rel="noopener noreferrer" target="_blank">Read more</a></li></ul> <ul><li>AI innovation grand challenge launched in COP28 to identify and support the development of AI-powered solutions for climate action in developing countries - <a href="https://unfccc.int/news/challenge-launched-at-cop28-to-harness-artificial-intelligence-for-climate-action-in-developing" rel="noopener noreferrer" target="_blank">Read more</a></li></ul> <ul><li>Blackrock to rollout generative AI tools to its clients in January. Blackrock manages over $9trillion in assets. - <a href="https://thepaypers.com/payments-general/blackrock-to-roll-out-genai-tools-to-its-clients--1265816" rel="noopener noreferrer" target="_blank">Read more</a></li></ul> The AI debate: <ul><li>NY times delves into what happened in OpenAI that ended in firing and rehiring of Sam Altman. NY times writes "as Mr. Altman raised OpenAI’s profile, some board members worried that ChatGPT’s success was antithetical to creating safe A.I.," - <a href="https://www.nytimes.com/2023/12/09/technology/openai-altman-inside-crisis.html" rel="noopener noreferrer" target="_blank" style="color: rgb(54, 54, 54);">Read more</a></li></ul> <ul><li>How AI ate the Internet this year - NewYorker - <a href="https://www.newyorker.com/culture/2023-in-review/the-year-ai-ate-the-internet" rel="noopener noreferrer" target="_blank">Read more</a></li></ul> <ul><li>Bitcoin and AI is leading in a new era of digital innovation, as highlighted by the integration of AI with Bitcoin's Lightning Network - <a href="https://www.forbes.com/sites/digital-assets/2023/12/08/ai-and-bitcoin--a-synergy-for-the-future/?sh=41b3007f6def" rel="noopener noreferrer" target="_blank">Read more</a></li></ul> <ul><li>The race to dominate AI - <a href="https://www.nytimes.com/2023/12/08/briefing/ai-dominance.html" rel="noopener noreferrer" target="_blank">Read more</a></li></ul>----Join Newnex - scale your investments and co-investments <a href="http://www.newnex.io" rel="noopener noreferrer" target="_blank">www.newnex.io</a>

Last week in Artificial Intelligence (AI)

EU becomes the first to adopt AI Act to regulate AI. The AI Act is a landmark regulation that aims to ensure that AI systems placed on the EU market are safe and respect fundamental rights.<ul><li>The regulation will be based on a risk-based approach.</li><li>High-risk AI systems will be subject to a strict set of requirements.</li><li>Banned AI practices will be prohibited.</li><li>There will be a new governance architecture with an AI Office at the EU level.</li><li>Penalties for violations of the AI Act will be significant.</li><li>There will be measures in support of innovation.</li><li>Rules have been agreed for foundation models, large systems capable to competently perform a wide range of distinctive tasks, such as generating video, text, images, conversing in lateral language, computing, or generating computer code.</li><li>Following the new rules on GPAI models and the obvious need for their enforcement at EU level, an&nbsp;AI Office&nbsp;within the Commission is set up tasked to oversee these most advanced AI models, contribute to fostering standards and testing practices, and enforce the common rules in all member states. </li><li>A scientific panel of independent experts&nbsp;will advise the AI Office about GPAI models, by contributing to the development of methodologies for evaluating the capabilities of foundation models, advising on the designation and the emergence of high impact foundation models, and monitoring possible material safety risks related to foundation models.</li><li>The provisional agreement provides for a&nbsp;fundamental rights impact assessment&nbsp;before a high-risk AI system is put in the market by its deployers.</li><li>The AI Act will apply two years after its entry into force.</li></ul> Industry's thoughts? In FT: "Cecilia Bonefeld-Dahl, director-general for DigitalEurope, which represents the continent’s technology sector, said: “We have a deal, but at what cost? We fully supported a risk-based approach based on the uses of AI, not the technology itself, but the last-minute attempt to regulate foundation models has turned this on its head." "France’s Airbus and Germany’s Siemens, said the rules as constituted were too tough to nurture innovation and help local industries" Access now has some interesting points:<a href="https://www.accessnow.org/press-release/historic-vote-in-the-european-parliament-dangerous-ai-surveillance-banned-but-not-for-migrant-people-at-the-borders" rel="noopener noreferrer" target="_blank">﻿https://www.accessnow.org/press-release/historic-vote-in-the-european-parliament-dangerous-ai-surveillance-banned-but-not-for-migrant-people-at-the-borders/</a> Information sources:<a href="https://www.consilium.europa.eu/en/press/press-releases/2023/12/09/artificial-intelligence-act-council-and-parliament-strike-a-deal-on-the-first-worldwide-rules-for-ai" rel="noopener noreferrer" target="_blank">https://www.consilium.europa.eu/en/press/press-releases/2023/12/09/artificial-intelligence-act-council-and-parliament-strike-a-deal-on-the-first-worldwide-rules-for-ai/</a> <a href="https://www.ft.com/content/d5bec462-d948-4437-aab1-e6505031a303" rel="noopener noreferrer" target="_blank">https://www.ft.com/content/d5bec462-d948-4437-aab1-e6505031a303</a>

EU adopts historic AI regulation

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