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SiliconANGLE AI

Rack-scale AI: How Dell and AMD are building infrastructure

Dell Technologies Inc. and its partner Advanced Micro Devices Inc. face similar competitive pressures. Both tech powerhouses operate in a business climate where success is now measured across central processing units, graphics processing units, rack-scale systems, memory capacity, network bandwidth and tokens per dollar. The pressure to compete across those measures underscores what theCUBE Research […] The post Rack-scale AI: How Dell and AMD are building infrastructure appeared first on SiliconANGLE.

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SiliconANGLE AI

Google, Anthropic and others to support new AI crawling opt-out standard

Google LLC, Microsoft Corp., Anthropic PBC and OpenAI Group PBC today announced plans to support an upcoming website crawling standard. The technology will enable website operators to block artificial intelligence developers from using their content to train their models. Many websites contain a text file titled “robots.txt” that informs crawlers what content they may access. […] The post Google, Anthropic and others to support new AI crawling opt-out standard appeared first on SiliconANGLE.

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SiliconANGLE AI

The race to deploy AI agents finds a familiar hurdle in data access

Enterprises racing to put AI agents into production are discovering that role-based access control, not model choice, decides whether those agents can be trusted. Rising inference costs, privacy worries and sovereignty demands are also pulling more AI workloads back inside corporate data centers. That shift favors companies that have spent years governing sensitive data at […] The post The race to deploy AI agents finds a familiar hurdle in data access appeared first on SiliconANGLE.

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SiliconANGLE AI

Dell expands cyber recovery tools to protect identity

Restoring data after a cyberattack isn’t enough if the identity systems that control access are compromised. Dell Technologies Inc. is extending its cyber recovery tools to cover those systems, putting identity resilience alongside data protection. That gap is widening as AI ties data, identity, infrastructure and applications into interdependent systems, making data protection a core […] The post Dell expands cyber recovery tools to protect identity appeared first on SiliconANGLE.

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llama.cpp releases

b11934

tests : speed up tensor data generation and model saving (#31145) * tests : speed up tensor data generation and model saving Refactor save_models to create only the model, not a llama_context, which is not needed for saving. Replace the slow std::normal_distribution draw with a splitmix64 + box-muller normal generator. Assisted-by: dsh:llama.cpp/ggml-org/DeepSeek-V4-Flash-Vision-Exp-GGUF (Mac Studio, M2 Ultra, 192GB) * tests : use a shared pool of normal draws for tensor data Generate a pool of normal draws once with std::mt19937 and std::normal_distribution, then have every tensor copy a cyclic slice of it instead of running a per-tensor box-muller. The name-keyed slice selection keeps the draw deterministic. Assisted-by: dsh:llama.cpp/ggml-org/DeepSeek-V4-Flash-Vision-Exp-GGUF (Mac Studi

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arXiv cs.AI

Financial Context-Rich Strategy for Actor-Critic based Agents: A Deep Reinforcement Learning Approach for Stock Trading

arXiv:2610.32237v1 Announce Type: new Abstract: In modern financial markets, more than 3/4th of the large volume trade is executed by algorithmic trading based on advanced trading strategies to attain higher precision and speed than traditional human traders. The conventional strategies focused on price-based indicators are inadequate in capturing the market dynamism arising from real-world events such as social sentiments, political instability, or sudden economic shifts. With the rise of Deep Reinforcement Learning (DRL) and data availability, there is a requirement for more efficient algorithms that can incorporate these external factors in trading strategies. DRL has shown potential in simulating real-world scenarios and in simplifying complex decision-making since DRL agents can autom

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