According to OpenAI... Ultrafast mode previews GPT-5.6 Sol at up to 14x speed, first via API to select customers, expanding as capacity grows.

According to @CNBC, Bank of America highlighted a lesser-known data provider as a way to play the AI boom, citing rising demand for training and inference.

According to @CNBC, Nvidia released Nemotron 3.5 Lightning as an open-source AI model to speed enterprise fine-tuning and reduce inference costs.

According to CNBC... Investors back Jensen Huang’s accelerated computing vision, spotlighting data center, inference, and software margins.

According to @CNBC, AMD acquired Taalas to hardwire AI models into silicon, aiming faster inference and lower power for edge and data centers.

According to JeffDean on X, napkin math that led to TPUs now points to inference hardware as the next specialization and a major energy challenge.

According to @CNBC, OpenAI cut prices for two GPT5.6 models, targeting cost-sensitive enterprises and boosting adoption of advanced AI workloads.

According to @CNBC, Zuckerberg detailed Meta’s AI capacity tradeoffs, weighing infrastructure sold to clients versus reserved for Meta products.

According to @CNBC, Alphabet shares rose after reports it is developing a more efficient AI chip to cut inference costs and boost model performance.

According to @CNBC, Fireworks reaches $17.5B valuation as enterprises seek cheaper, domain-tuned models to cut AI inference costs and vendor lock-in.

According to @CNBC, Chamath warns rising AI token spend will compress margins and dent 2026 earnings, pressuring firms reliant on GPT4 class models.

According to TheRundownAI, OpenAI found a compute multiplier cutting inference costs by half, per The Information, alongside its Jalapeño chip with Broadcom.

According to @CNBC, enterprises now prefer efficient AI usage over token volume, pressuring OpenAI and Anthropic to cut costs and boost throughput.

According to @CNBC, Anthropic’s hiring shows new AI data centers planned across five global hubs, signaling infrastructure scale-up and enterprise growth.

According to @OpenAI, Broadcom will co-develop a Jalapeno inference chip to cut AI serving costs and latency, as reported by OpenAI’s blog.

According to @CNBC, OpenAI revealed Jalapeno, its first AI chip with Broadcom, targeting full-stack control and lower inference costs.

According to @CNBC, an AI memory startup raised $98M to cut token costs, aiming to lower LLM inference spend for enterprises, per CNBC reporting.

According to KyeGomezB, a deep dive details Anthropic’s Claude production stack, covering architecture, infra, and deployment systems, with engineering sources.

According to Jeff Dean, Gemini 3.5 Flash balances speed and capability for rapid AI inference and strong task performance.

According to @OpenAI, Guaranteed Capacity offers contracted access to OpenAI compute for reliable long term scaling, backed by infrastructure investments.