Destination
Ex-OpenAI researcher bets $100 billion will flow into training data because scaling alone won't cut it

Former OpenAI employee Andrew Ho and Cambridge researcher Adam Hunt see a growing problem with large language models. Instead of becoming more versatile, the models are becoming more specialized, excelling at coding and math while stagnating or even regressing in other areas. Ho is leaving OpenAI to start a company focused on specialized training data and predicts that AI labs will need to spend more than $100 billion on targeted data collection.<br /> The article Ex-OpenAI researcher bets $100 billion will flow into training data because scaling alone won't cut it appeared first on The Decoder. [...]

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venturebeat
Black Forest Labs' new Self-Flow technique makes training multimodal AI models 2.8x more efficient

To create coherent images or videos, generative AI diffusion models like Stable Diffusion or FLUX have typically relied on external "teachers"—frozen encoders like CLIP or DINOv2—to prov [...]

Match Score: 106.41

venturebeat
Microsoft and OpenAI gut their exclusive deal, freeing OpenAI to sell on AWS and Google Cloud

Microsoft and OpenAI on Monday announced a sweeping overhaul of the partnership that has defined the commercial AI era, dismantling key pillars of exclusivity and revenue-sharing that bound the two co [...]

Match Score: 97.87

venturebeat
Train-to-Test scaling explained: How to optimize your end-to-end AI compute budget for inference

The standard guidelines for building large language models (LLMs) optimize only for training costs and ignore inference costs. This poses a challenge for real-world applications that use inference-tim [...]

Match Score: 96.99

venturebeat
Baseten takes on hyperscalers with new AI training platform that lets you own your model weights

Baseten, the AI infrastructure company recently valued at $2.15 billion, is making its most significant product pivot yet: a full-scale push into model training that could reshape how enterprises wean [...]

Match Score: 94.33

venturebeat
OpenAI deploys Cerebras chips for 15x faster code generation in first major move beyond Nvidia

OpenAI on Thursday launched GPT-5.3-Codex-Spark, a stripped-down coding model engineered for near-instantaneous response times, marking the company's first significant inference partnership outsi [...]

Match Score: 82.83

Destination
Engadget's favorite games of 2025

From indies like Silksong, to AAAs like Ghost of Yotei, and everything in between, 2025 truly had it all, and is likely to go down in the history books as one of the best years in gaming. But these ar [...]

Match Score: 82.45

venturebeat
Phi-4 proves that a 'data-first' SFT methodology is the new differentiator

AI engineers often chase performance by scaling up LLM parameters and data, but the trend toward smaller, more efficient, and better-focused models has accelerated. The Phi-4 fine-tuning methodology [...]

Match Score: 76.94

Destination
Everything announced and all the winners at The Game Awards 2025

This year at The Game Awards, if your game wasn’t melodramatic, mechanically innovative, beautifully presented and aggressively French, it didn’t stand a chance. The Game Awards 2025 wrapped up on [...]

Match Score: 75.87

venturebeat
Moonshot’s Kimi K2.5 is 'open,' 595GB, and built for agent swarms — Reddit wants a smaller one

Two days after releasing what analysts call the most powerful open-source AI model ever created, researchers from China's Moonshot AI logged onto Reddit to face a restless audience. The Beijing-b [...]

Match Score: 75.76