Google has released multi-token prediction drafters for its Gemma 4 open model family that speed up text generation by up to three times. A small auxiliary model suggests several tokens at once while the main model checks them in a single pass.<br /> The article Google speeds up Gemma 4 threefold with multi-token prediction appeared first on The Decoder. [...]
For the past two years, enterprises evaluating open-weight models have faced an awkward trade-off. Google's Gemma line consistently delivered strong performance, but its custom license — with u [...]
As agentic AI workflows multiply the cost and latency of long reasoning chains, a team from the University of Maryland, Lawrence Livermore National Labs, Columbia University and TogetherAI has found a [...]
The recent controversy surrounding Google’s Gemma model has once again highlighted the dangers of using developer test models and the fleeting nature of model availability. Google pulled its Gemma [...]
When Google released Gemini 3 Pro at the end of last year, it was a significant step forward for the company's proprietary large language models. Now, the company is bringing some of the same tec [...]
Kalshi can't be stopped in New Jersey. A 3rd US Circuit Court of Appeals panel ruled on Monday that New Jersey has no authority to regulate Kalshi's prediction market allowing people to bet [...]
For the last 24 months, one narrative justified every over-provisioned data center and bloated IT budget: the GPU scramble. Silicon was the new oil, and H100s traded like contraband. Reserve capacity [...]
Enterprise teams building multi-agent AI systems may be paying a compute premium for gains that don't hold up under equal-budget conditions. New Stanford University research finds that single-age [...]