Apple Inc. reached a $5 trillion market capitalization milestone as investors rotate away from AI pure-play stocks, reflecting a market shift from AI training to inference and deployment. The move tow…
Nvidia's market strategy faces a hardware bottleneck as government trade restrictions force the company to create 'lite' versions of its H100 and B200 chips, such as the H20, to meet legal requirement…
AI chip stocks are experiencing a market correction driven by capex fatigue, concentration risk among cloud service providers, and expectation inflation, according to an analysis of the current cycle.…
Nvidia's investment strategy creates a circular AI loop where the company invests in startups, which then use the capital to buy Nvidia GPUs, boosting Nvidia's revenue and the startups' valuations, ac…
South Korea's KOSPI market is experiencing a crash driven by AI chip volatility and investor fear, as the narrative shifts from a 'buy everything AI' mentality to demanding proof of productivity from …
Moonshot AI released the full Kimi K3 open weights on July 27, 2026, a 2.8-trillion-parameter mixture-of-experts model with a one-million-token context window and a 1.4 TB download. The model uses nat…
Fermion Research released Neutrino-1 8B, a 3.88 GB language model trained natively with ternary weights ({-1, 0, +1}) that achieves 763 tokens per second on an H100 with speculative decoding and 24.9 …
A new analysis predicts that AI models will grow from 10 trillion parameters in 2026 to 1.4 quadrillion parameters by 2031, with inference costs remaining surprisingly low due to KV cache scaling. The…
Moonshot AI released the open weights of its 2.8-trillion-parameter Kimi K3 sparse Mixture-of-Experts model on Hugging Face under an Apache 2.0 license, but the 594 GB MXFP4-quantized model requires a…
OpenLake, an open-source storage engine for offloading LLM KV caches from GPU memory to RAM and NVMe, cuts GPU time by 48.2% for long-context inference, reducing a 1,169-second workload to 606 seconds…
Etched, a chip startup founded by three Harvard dropouts, closed a $300 million Series C at a $10.3 billion valuation on July 23, led by Sequoia, to produce its Sohu ASIC that hardwires transformer mo…
Google has developed a new custom AI chip designed specifically for its Gemini large language model, aiming to drastically reduce inference costs and latency by addressing the memory wall and power in…
The Genesis Mission represents a $5 billion pivot in U.S. science policy toward AI, robotics, and nuclear energy, sidelining traditional life sciences. Michael Kratsios, the primary advocate for this …
NVIDIA Research's Efficient AI Team and Singapore Lab introduced SANA-Video 2.0, a hybrid video diffusion transformer at 5B and 14B scales that generates 720p video on a single H100 GPU. The model ach…
Etched, a startup founded in 2022, has partnered with Andreessen Horowitz to build purpose-built AI inference hardware, raising approximately $800 million in total funding and securing over $1 billion…
A surge in demand for non-Nvidia AI chips is reshaping hardware strategies as engineers optimize large language model deployments for alternative architectures due to H100 shortages and high costs. Th…
AWS raised H200 GPU instance prices by 15% on January 4, 2026, the first GPU price increase in roughly two decades, while average GPU utilization across more than 23,000 Kubernetes clusters sits at ju…
A developer argues that the real money in AI is in the physical infrastructure layer—chips, servers, power, and cooling—not the chatbots. Using Groq as an example, the piece explains the 'memory wall'…
Unsloth achieves up to 7.3x training speedup over standard Transformers for MoE models like gpt-oss-20B on an NVIDIA B200, according to published benchmarks, while Axolotl delivers up to 1.45x speedup…
Cisco Foundation AI released Antares, a family of small language models (350M and 1B parameters) that localize known vulnerabilities inside real codebases. Antares-1B achieves 0.209 File F1 on the Vul…