AI Hardware AI News & Updates
AMD Secures Massive Multi-Billion Dollar AI Chip Deal with OpenAI for 6GW Compute Capacity
AMD has signed a major multi-year deal with OpenAI to supply 6 gigawatts of compute capacity using its Instinct GPU series, potentially worth tens of billions of dollars. The agreement includes an option for OpenAI to acquire up to 160 million AMD shares (10% stake), with deployment beginning in late 2026 using the new MI450 GPU. This deal is part of OpenAI's aggressive expansion to secure compute infrastructure for AI development, following similar recent partnerships with Nvidia, Broadcom, and others.
Skynet Chance (+0.01%): Massive compute expansion enables training of more powerful AI systems with potentially less oversight due to distributed infrastructure, though this is primarily a capability scaling concern rather than a direct alignment or control issue. The impact is modest as it represents expected industry trajectory.
Skynet Date (-1 days): The deployment of 6GW of additional compute capacity starting in 2026 modestly accelerates the timeline for developing more capable AI systems that could pose control challenges. However, the 2026 start date means immediate impact is limited.
AGI Progress (+0.03%): This massive compute infrastructure investment directly addresses one of the key bottlenecks to AGI development—access to sufficient computational resources for training frontier models. The 6GW capacity represents a substantial scaling of OpenAI's training and inference capabilities.
AGI Date (-1 days): Securing guaranteed access to 6GW of compute capacity removes a major constraint on OpenAI's ability to rapidly scale model development and experimentation. This represents significant acceleration in OpenAI's AGI timeline, though deployment begins in 2026 rather than immediately.
Naveen Rao Raises Hundreds of Millions for Brain-Inspired AI Hardware Startup at $5B Valuation
Naveen Rao, former head of AI at Databricks, is raising $1 billion at a $5 billion valuation for Unconventional, Inc., a startup building novel AI computing hardware inspired by biological efficiency. Led by Andreessen Horowitz with participation from Lightspeed and Lux Capital, the company aims to compete with Nvidia by designing custom silicon chips and server infrastructure. Rao has already raised hundreds of millions and plans to begin building immediately using a tranched funding approach.
Skynet Chance (+0.01%): Alternative hardware architectures could potentially enable more distributed AI development beyond current centralized control points, though biological-inspired designs may also improve alignment properties. The net effect on control and safety is uncertain at this stage.
Skynet Date (-1 days): Significant capital investment in novel AI hardware could accelerate overall AI capability development by diversifying compute approaches and potentially overcoming current bottlenecks. However, the technology is still in early development stages with uncertain timelines to deployment.
AGI Progress (+0.02%): Brain-scale efficiency computing represents a potential breakthrough in overcoming current power and scaling limitations of AI systems, addressing a fundamental constraint to AGI development. The substantial $5B valuation and backing from top VCs signals confidence in the technical approach's viability.
AGI Date (-1 days): The massive capital deployment ($1B raise) and focus on fundamentally rethinking computer architecture for AI could accelerate AGI timelines if successful, though hardware development typically requires 3-5+ years. Competition with Nvidia suggests potential for breaking current compute monopolies that may be constraining progress.
Nvidia Reports $46.7B Revenue Quarter as CEO Predicts $3-4 Trillion AI Infrastructure Market
Nvidia reported $46.7 billion in quarterly revenue, representing a 56% year-over-year increase driven by AI demand. CEO Jensen Huang predicted $3-4 trillion in global AI infrastructure spending over the next five years, though the stock declined as investors questioned the sustainability of such growth rates.
Skynet Chance (+0.04%): Massive compute scaling through unprecedented infrastructure investment could enable more powerful AI systems with greater potential for unintended consequences. The sheer scale of predicted spending ($3-4 trillion) suggests AI capabilities may advance faster than safety measures.
Skynet Date (-1 days): Nvidia's massive revenue growth and predictions of trillions in AI infrastructure spending indicate significant acceleration in AI development timelines. The scale of hardware deployment could compress the timeline for advanced AI risks to emerge.
AGI Progress (+0.03%): Record-breaking revenue and predictions of massive infrastructure investment directly indicate accelerated progress toward AGI through enhanced compute availability. The 56% growth rate and multi-trillion dollar market projections suggest rapid scaling of AI capabilities.
AGI Date (-1 days): Nvidia's explosive growth and Jensen Huang's trillion-dollar infrastructure predictions strongly suggest accelerated AGI timelines. The massive compute scaling enabled by this investment level could significantly compress the time needed to achieve AGI.
Nvidia Reports Record $46.7B Revenue Driven by AI Data Center Demand and Blackwell Chip Success
Nvidia reported record quarterly revenue of $46.7 billion, representing a 56% year-over-year increase, primarily driven by AI data center business growth. The company's advanced Blackwell chips accounted for $27 billion in sales, with CEO Jensen Huang positioning Blackwell as the central platform in the ongoing "AI race." Geopolitical tensions continue to impact Chinese market sales despite new arrangements allowing exports with a 15% tax.
Skynet Chance (+0.04%): Massive GPU scaling accelerates AI capability development, potentially increasing risks of uncontrolled AI systems as more powerful compute becomes widely available. However, this represents expected hardware progression rather than a fundamental safety breakthrough or failure.
Skynet Date (-1 days): Accelerated GPU production and deployment speeds up AI development timelines across the industry. The scale of compute availability ($41B in data center revenue) suggests faster capability advancement than previously anticipated.
AGI Progress (+0.03%): Record GPU sales and Blackwell chip performance directly enable larger AI model training and inference, representing significant progress in compute scaling essential for AGI development. The mention of processing "1.5 million tokens per second" demonstrates substantial capability advancement.
AGI Date (-1 days): The unprecedented scale of AI hardware deployment ($27B in Blackwell sales alone) significantly accelerates the timeline for AGI development by removing compute bottlenecks. This level of hardware availability enables faster experimentation and larger model development across the industry.
OpenAI Acquires Jony Ive's Device Startup for $6.5B to Develop AI Hardware
OpenAI acquired Jony Ive and Sam Altman's device startup "io" for $6.5 billion in an all-equity deal. The legendary Apple designer will lead creative work at OpenAI through his firm LoveFrom to develop AI-powered consumer devices that go "beyond the screen."
Skynet Chance (+0.01%): The move towards AI-powered consumer devices could increase AI integration into daily life, but focuses on user experience rather than advancing core AI capabilities or creating alignment risks.
Skynet Date (+0 days): This acquisition primarily addresses product design and consumer hardware rather than accelerating or decelerating fundamental AI research that would affect risk timelines.
AGI Progress (+0.01%): The substantial investment in AI hardware development represents a significant step toward making AI more accessible and integrated into consumer products, advancing practical AGI deployment.
AGI Date (+0 days): The major financial commitment and focus on consumer AI devices suggests OpenAI is accelerating its timeline for widespread AI deployment, though this is primarily about productization rather than core research.
AI Data Centers Projected to Reach $200 Billion Cost and Nuclear-Scale Power Needs by 2030
A new study from Georgetown, Epoch AI, and Rand indicates that AI data centers are growing at an unprecedented rate, with computational performance more than doubling annually alongside power requirements and costs. If current trends continue, by 2030 the leading AI data center could contain 2 million AI chips, cost $200 billion, and require 9 gigawatts of power—equivalent to nine nuclear reactors.
Skynet Chance (+0.04%): The massive scaling of computational infrastructure enables training increasingly powerful models whose behaviors and capabilities may become more difficult to predict and control, especially if deployment outpaces safety research due to economic pressures.
Skynet Date (-1 days): The projected doubling of computational resources annually represents a significant acceleration factor that could compress timelines for developing systems with potentially uncontrollable capabilities, especially given potential pressure to recoup enormous infrastructure investments.
AGI Progress (+0.05%): The dramatic increase in computational resources directly enables training larger and more capable AI models, which has historically been one of the most reliable drivers of progress toward AGI capabilities.
AGI Date (-1 days): The projected sustained doubling of AI compute resources annually through 2030 significantly accelerates AGI timelines, as compute scaling has been consistently linked to breakthrough capabilities in AI systems.
Nvidia Faces Growing Challenges Despite Record GTC Attendance and New Product Launches
At GTC 2025, Nvidia unveiled new chips and products to a record 25,000 attendees while addressing growing challenges including U.S. tariffs, emerging competitors like DeepSeek, and AI clients developing in-house alternatives. CEO Jensen Huang emphasized that reasoning models will increase demand for Nvidia chips and announced plans for U.S. manufacturing investments to address potential supply chain issues.
Skynet Chance (0%): While Nvidia's new chips may accelerate AI development, this news primarily concerns business positioning and hardware manufacturing rather than introducing capabilities that would specifically increase or decrease AI control risks, and thus has negligible impact on Skynet probability.
Skynet Date (+0 days): The developments described are primarily about market competition and business adaptations rather than technological breakthroughs that would substantially alter the timeline for advanced AI capabilities, having minimal effect on when potential AI risk scenarios might emerge.
AGI Progress (+0.01%): Nvidia's new Vera Rubin GPUs with doubled inference capabilities represent an incremental advance in AI hardware that will support more powerful models, though the primary focus appears to be on business positioning rather than revolutionary technical capabilities.
AGI Date (+0 days): The competitive dynamics described—including Nvidia's response to reasoning models and announcement of faster inference chips—could moderately accelerate AI development timelines by ensuring continued hardware advancement despite emerging market challenges.
Nvidia Prepares to Unveil Next-Generation AI Hardware at GTC 2025
Nvidia's annual GTC conference is set to feature announcements of next-generation AI hardware, including the upgraded Blackwell B300 series (Blackwell Ultra) and details about the future Rubin GPU architecture. Despite recent challenges with overheating issues and stock price pressure, Nvidia remains dominant with 82% of the GPU market and recently reported record-breaking quarterly revenue of $39.3 billion.
Skynet Chance (+0.05%): The significant leap in computing power represented by Blackwell Ultra and subsequent Rubin architectures enables increasingly sophisticated AI models that could exceed human understanding and monitoring capabilities, potentially creating systems whose behaviors become less predictable and harder to control.
Skynet Date (-2 days): The continuous acceleration of AI compute capabilities represented by these new GPU architectures directly shortens the timeline for developing systems with potential control risks, as the hardware enabling more powerful and potentially autonomous systems is becoming available much sooner than previously projected.
AGI Progress (+0.09%): The introduction of significantly more powerful GPU architectures like Blackwell Ultra and Rubin represents a substantial step toward enabling the training of more capable AI systems, as compute capacity has been historically one of the most reliable predictors of AI capability advances.
AGI Date (-2 days): Nvidia's rapid acceleration of next-generation AI hardware development, with Blackwell Ultra coming in 2025 and already discussing post-Rubin architectures, significantly compresses the timeline for when sufficient computational resources for AGI will be widely available to researchers and companies.
Nvidia GTC 2025 Conference Begins with Anticipated Major Hardware Announcements
Nvidia's GTC 2025 conference has commenced with expected announcements about new AI hardware, including Blackwell Ultra processors and partnerships with GM. The event will feature updates on Nvidia's next-generation computing platforms, described as "personal AI supercomputers."
Skynet Chance (0%): This announcement merely indicates the conference has started with expected announcements, but contains insufficient details about actual technologies or their implications to assess any meaningful impact on AI control risks or safety concerns.
Skynet Date (+0 days): The article contains no substantive information about the announced technologies' capabilities or deployment timelines, providing insufficient data to assess how these announcements might affect the pace of development toward potentially uncontrollable AI systems.
AGI Progress (0%): While the conference is likely to feature significant AI hardware announcements, this specific article contains no actual technical details about the new technologies, making it impossible to assess their concrete impact on AGI progress.
AGI Date (+0 days): Without specific details about the capabilities, performance improvements, or availability of the mentioned hardware, there is insufficient information to determine how these announcements might affect the timeline toward AGI development.
OpenAI Trademark Filing Reveals Plans for Humanoid Robots and AI Hardware
OpenAI has filed a new trademark application with the USPTO that hints at ambitious future product lines including AI-powered hardware and humanoid robots. The filing mentions headphones, smart glasses, jewelry, humanoid robots with communication capabilities, custom AI chips, and quantum computing services, though the company's timeline for bringing these products to market remains unclear.
Skynet Chance (+0.06%): OpenAI's intent to develop humanoid robots with 'communication and learning functions' signals a significant step toward embodied AI that can physically interact with the world, increasing autonomous capabilities that could eventually lead to control issues if alignment isn't prioritized alongside capabilities.
Skynet Date (-1 days): The parallel development of hardware (including humanoid robots), custom AI chips, and quantum computing resources suggests OpenAI is building comprehensive infrastructure to accelerate AI embodiment and processing capabilities, potentially shortening the timeline to advanced AI systems.
AGI Progress (+0.03%): The integrated approach of combining advanced hardware, specialized chips, embodied robotics, and quantum computing optimization represents a systematic attempt to overcome current AI limitations, particularly in real-world interaction and computational efficiency.
AGI Date (-1 days): Custom AI chips targeted for 2026 release and quantum computing optimization suggest OpenAI is strategically addressing the computational barriers to AGI, potentially accelerating the timeline by enhancing both model training efficiency and real-world deployment capabilities.