Advancing AMIE towards expert-level audio-visual clinical consultations
Health & Bioscience
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The memory wall: Why your GPUs are sitting idle
As generative AI shifts from coaching to enterprise-scale inference, a hidden bottleneck is placing ROI in danger. GPUs supply immense computational energy, however they’re ceaselessly constrained by memory limitations. According to Penguin Solutions, this may go away costly compute cycles as much as 70% idle. The result’s a “memory wall” that will get worse as…
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Data Infrastructure Summit Virtual Summit | May 2026
Catch on each session from Data Infrastructure Summit, with periods from the likes of USBank, Betterworks, Meta, ServiceNow and extra.
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Building and Validating a Quantitative Trading Strategy with OctoBot, Walk-Forward Backtesting, Parameter Optimization, and Interactive Analysis
In this tutorial, we construct a full quantitative backtesting workflow with OctoBot and OctoBot-Script whereas protecting the surroundings remoted from Colab’s preinstalled dependencies. We configure a rule-based buying and selling technique that mixes RSI-based oversold indicators, EMA pattern affirmation, and ATR-driven adaptive stop-loss and take-profit ranges, and we execute it by OctoBot’s native market-order and…
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Novo Nordisk and AWS bring agentic AI into drug discovery
Novo Nordisk is increasing its use of AWS synthetic intelligence instruments throughout drug discovery, together with AI brokers for goal identification, remedy design, and analysis workflows. Under the settlement introduced not too long ago, AWS will grow to be Novo Nordisk’s most popular cloud supplier and strategic AI associate. The corporations have additionally created a…
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How AI is changing the vulnerability response timeline
Artificial intelligence is giving safety researchers new methods to look at code, hint uncommon behaviour and determine flaws that standard instruments might overlook. The stress is significantly seen round Zero-day vulnerabilities, a latest Minimus evaluation considers how container composition, dependency data and rebuild velocity have an effect on the response after an unknown flaw is uncovered….
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webAI Releases TwIL-LM: A 1.7B and 3B Formal-Logic Model Family for Autoformalization on Local Hardware
webAI has launched TwIL-LM, a two-model family of formal-logic reasoners at 1.7B and 3B parameters. The 3B member, TwIL-LM3, is a merged fine-tune of SmolLM3-3B; the 1.7B member is a PEFT LoRA adapter for SmolLM2-1.7B-Instruct. Both goal autoformalization: translating English into first-order logic and checking whether or not a conclusion follows from its premises. Both…
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Implementing a MiniMax-H3 Multimodal Video and Audio Generation Pipeline with ComfyUI APIs
In this tutorial, we implement an end-to-end MiniMax-H3 video technology workflow utilizing ComfyUI as a headless inference backend. We configure the atmosphere round GPU reminiscence, disk capability, mannequin precision, decision, length, sampling technique, and a number of technology modes, whereas dynamically deciding on an applicable weight profile primarily based on the accessible {hardware}. We set…
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6 mistakes AI leaders keep making with agentic deployments
The hole between ambition and infrastructure Gartner expects over 40% of agentic AI projects to get canceled by the tip of 2027, a June 2025 prediction pushed by rising prices, murky enterprise worth, and skinny threat controls. MIT’s State of AI in Business 2025 report printed that August discovered 95% of generative AI pilots fail…
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Meta AI Releases Muse Glimmer: A 30B Open-Weights Agentic Model That Runs on One Consumer GPU
Meta has launched Muse Glimmer, a 30-billion-parameter multimodal mannequin distilled from Muse Spark. It is tuned for always-on native agent workflows, and ships underneath Apache 2.0. A 30B mannequin usually wants over 55 GB of reminiscence at full precision. Meta compresses it to roughly 4-bit, then provides block-level speculative decoding so it solutions quick sufficient…
