230. MCP - It's Hot, But Will It Win?
There's a long history of "middleware" in our industry. Everyone wants it. There's always a hot one, but it rarely makes to the finish line and often disappoints.
Jan-Nano : 1st Deep Research LLM
Accelerating Scientific Research with Gemini in the Real-World
We present an extension and comprehensive real-world validation of Co-Scientist, a Gemini-based multi-agent system designed to accelerate end-to-end scientific research across hypothesis generation, experimentation, and manuscript generation. Moving beyond in silico hypothesis generation, this specialized configuration transitions Co-Scientist into an execution-grounded research partner advancing closed-loop scientific workflows across materials science, biology, and computer science. In materials science, Co-Scientist interfaced with a semi-automated chemical vapor deposition reactor to design a safe precursor route for MXenes; experimental execution produced a lamellar 2D material sharing key structural similarities with the Ti3C2Tx MXene lattice, although further experiments are needed to confirm the atomic structure. Leveraging Gemini 3 Deep Think for rapid, lab-in-the-loop execution, it also tailored growth recipes to laboratory constraints in minutes, enabling single-attempt growth of monolayer MoS2, MoSe2, and WS2 semiconductors. In biology, Co-Scientist predicted emergent swarming phenotypes of engineered E. coli across inducer (IPTG) gradients from sparse imaging data, quantitatively matching unpublished wet-lab morphological measurements. In computer science, Co-Scientist autonomously discovered an inference-time scaling architecture that outperformed six frontier models on HealthBench (Hard and Professional) while reducing potential clinical harm under blinded physician evaluation. Finally, a double-blind study of end-to-end generated papers with 30 domain experts across 450 reviews demonstrates that Co-Scientist's reliability modules reduce hallucination and plagiarism while improving research safety. Together, these results demonstrate progress toward closed-loop multi-agent scientific AI systems capable of accelerating real-world scientific discovery.
apple-silicon-llm-bench/results/complete_results.html at main · AlexHiesch/apple-silicon-llm-bench
Systematic LLM inference benchmark for Apple Silicon: 8 backends, 7 models, 791 measurements - AlexHiesch/apple-silicon-llm-bench
Release v0.29.0 · ml-explore/mlx
Highlights Support for mxfp4 quantization (Metal, CPU) More performance improvements, bug fixes, features in CUDA backend mx.distributed supports NCCL back-end for CUDA What's Changed [CUDA]...
Megakernel: Matching Apple Silicon Efficiency at 2x the Throughput on a RTX 3090
The first megakernel for hybrid DeltaNet/Attention LLMs. 413 tok/s at 1.87 tok/J on a 2020 RTX 3090, matching M5 Max efficiency at 1.8x throughput.
unsloth/Jan-nano-128k-GGUF · Hugging Face
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
IOSP 2026: Institute of Open Science Practices (space) | nanodash
An event, a community, and a coordinating institute for the people building, using, and advancing the infrastructure open science depends on. IOSP 2026 is the third edition, held 12-15 October 2026 in Leiden: the Poortgebouw of the University of Leiden and GO FAIR host 12, 13 and 15 October, while 1…
Running local models on an M4 with 24GB memory | jola.dev
Experiments with getting usable outputs out of local models on a standard Macbook
Apple JUST Dropped a Game-Changer
MacBook Air (M4)
The MacBook Air with the M4 chip is Apple's most powerful yet, with amazing battery life and buttery-smooth performance in a thin and light profile.
Cua on Twitter / X
1/ Today, as part of our broader research into Apple Silicon virtualization, we're releasing a process-scoped Metal capability layer for macOS VMs. On one M1 Ultra, prompt / generation:TinyLlama: 11.08× / 16.36×Gemma 4 12B: 7.20× / 14.54×Muse Glimmer 30B: 7.55× / 8.87× pic.twitter.com/6UwxgoDowT— Cua (@trycua) August 11, 2026
On Kimi K3: Its Capabilities And Related Discontents
Kimi K3 is a very good model with excellent benchmarks.
