alan blount retweeted
Just wanted to share a (very much WIP) little side project of mine showcasing the benefits/speed of @googlegemma DiffusionGemma 🙂 (text diffusion model)
Project is called “DiffusionGearvis” (mix between DiffusionGemma and Jarvis, IronMan’s AI assistant) and I wanted to implement some features for which I believe text diffusion can really shine, the first one being computer use.
With the success of Muse from Meta, it is very clear that computer use has tremendous value for users. However, this feature is 1) notoriously slow 2) raises serious privacy concerns (screenshots and other personal data uploaded to the cloud). DiffusionGemma can help with both 🙂 It is super fast thanks to text diffusion and is open-weight so people can run it privately on their own desktop / VM. All the demo videos were run locally on a desktop with a single @NVIDIAAIDev RTX 5090 with speech-to-text and text-to-speech from @kyutai_labs (stt-1b-en_fr and pocket_tts) .
This is with the vanilla NVFP4 checkpoint served on @vllm_project so performance can vastly be improved with dedicated fine-tuning or distillation from larger open-weights models. I hope that in a few months, the open-source community will create some fast “local Muse” on top of it :
alan blount retweeted
Muse Spark Open from @Meta is now available on the Gemini platform.
Meta's coding-optimized open-weight model is available for developers building long-running agentic coding workflows.
Try Muse Spark Open now → goo.gle/4zvPTXL
alan blount retweeted
Google’s new Gemini 4 Argon equals GPT-6 Astra on the Artificial Analysis Intelligence Index at 60% of the Cost per Task with discounted prices. Google is now back to being one of the top three labs in intelligence achieved
Gemini 4 Argon is @GoogleDeepMind’s first proprietary model above the Flash class in over 7 months. With high reasoning (the highest available), it scores 53 on the Artificial Analysis Intelligence Index, matching GPT-6 Astra (max, 53) and 1 point ahead of GPT-6.1 Sol (max, 52), with gains driven by lower hallucinations and stronger agentic capabilities.
At its current 50% pricing discount and with cache discounts increased to 95%, Gemini 4 Argon costs $1.99 per Intelligence Index task, 60% of GPT-6 Astra (max), but 2.7x GPT-6.1 Sol (max). After the discount ends, this will rise to $3.98 (~1.2x GPT-6 Astra (max)).
Gemini 4 Argon is currently being rolled out to selected users and is not publicly available. The 50% discount is an initial promotion. Google has not yet confirmed the promotion end date
Key benchmarking results for Gemini 4 Argon with high reasoning:
➤ Google returns as one of the top three labs on intelligence: Gemini 4 Argon (high) scores 53 on the Artificial Analysis Intelligence Index, matching GPT-6 Astra (max, 53) and 1 point ahead of GPT-6.1 Sol (max, 52). This is 23 points above Google’s previous non-Flash model, Gemini 3.1 Pro Preview (30) and 12 points ahead of Gemini 3.8 Flash (high)
➤ Launch discounts of 50% make Gemini 4 Argon competitive on Cost per Task: At current discounted pricing, Gemini 4 Argon (high) costs $1.99 per Intelligence Index task, 60% of GPT-6 Astra (max, $3.26) for a comparable level of intelligence. This cost efficiency is driven by lower token prices, rather than reduced token use, with Gemini 4 Argon averaging 62k output tokens per task, compared with 27k for GPT-6 Astra (max). Google has not yet confirmed the promotion end date, but on standard pricing, Cost per Task will increase to $3.98
➤ Stronger agentic performance: Historically a weaker area for Gemini models, Gemini 4 Argon shows improvements across agentic evaluations. It ranks #1 on AutomationBench-AA at 77.5%, 6 points ahead of Claude Sonnet 5.5 (max, 71.3%). On Terminal Bench 4, Gemini 4 Argon achieves 57%, a +53 point improvement from Gemini 3.1 Pro Preview, only behind Claude Sonnet 5.5 (max, 64%), Claude Opus 5.5 (max, 60%) and GPT-6 Astra (59%). On AA-Briefcase, it reaches 1494 Elo. This is driven by a 65% rubric pass rate, the highest we have recorded, but lower Analytical Quality (1576 Elo) and Presentation Quality (1308 Elo)
➤ Lowest hallucination rate among leading models: On AA-Omniscience, Gemini 4 Argon has a 15% hallucination rate, the lowest of any model scoring 45+ on the Intelligence Index, compared with 51% for GPT-6 Astra (max) and 54% for GPT-6.1 Sol (max). This means Argon is much more likely to acknowledge when it does not know an answer rather than guess incorrectly. On accuracy, Gemini 4 Argon scores 50%, a 5 point decrease from Gemini 3.1 Pro Preview, and 13 points below GPT-6 Astra (max, 63%). With this slightly lower accuracy, its overall AA-Omniscience score of 42 remains in line with GPT-6 Astra (43) and GPT-6.1 Sol (42)
Key model details:
➤ Context Window: 1M tokens
➤ Multimodality: Text, image, video, and speech input, with text output
➤ Pricing: $4/$20 per 1M input/output tokens at standard pricing, currently discounted 50% to $2/$10. Cached input tokens receive a 95% discount ($0.10 per 1M at discounted pricing), up from 90% on Gemini 3.8 Flash
➤ Long Decode Continuation: We tested Gemini 4 Argon with Long Decode Continuation, a new Gemini API feature that pauses long responses and resumes them across follow-up calls. This lets reasoning run up to 1M output tokens without request timeouts
alan blount retweeted
Introducing Gemini 3.8 Live and 3.8 Live Extended Thinking 🚀
Excited for these two SOTA live audio models with frontier price and performance.
Extended thinking can run tool calls and think in parallel, which makes it incredibly cool and smooth to use 👇
🤖 Made with AI
alan blount retweeted
Today, we’re announcing the general availability of extended capabilities in Gemini Enterprise Agent Platform!
Take full advantage of our centralized, end-to-end platform to simply and securely scale and manage your agents and workflows → goo.gle/3RYp6Dv
Python, MCP, A2A, and a whole lot about how to build multi-agent systems.
This goes well beyond building a single agent: it focuses on how multiple agents can collaborate towards a goal.
Best part:
The book will show you how to build everything from scratch. You start with a simple agent and then add complexity as the book progresses.
Amazon link: amzn.to/3OVgk7M
alan blount retweeted
📢Berkeley Function Calling Leaderboard Update: Discover the enhanced performance and cost-efficiency of @GoogleDeepMind's Gemini-1.5-pro and Gemini-1.5-flash, alongside @OpenAI's new gpt-4o models ⚡️Gemini sets a new benchmark in function-calling 🏆and improves its capabilities in relevance detection - ability to say NO! Parallel-multiple function calls continue to be elusive 👀
Play around: gorilla.cs.berkeley.edu/lead…
alan blount retweeted
My favorite paper for reflecting on before the New Year asks the key question: how can we be happier?
The world's top happiness scholars ranked the best strategies for individual & societal happiness, here are results listed by feasibility & effectiveness link.springer.com/article/10…
alan blount retweeted
Any friends not vaxxed yet for non medical reasons and want to talk it out without judgement? Happy to answer any questions or just listen to you if you need to work though some anxiety. – at Manhattan, NY
alan blount retweeted
Like all of you, I’ve been feeling so many emotions since yesterday. I tried to put my thoughts down here:
alan blount retweeted
The US election is tomorrow. If you, like me, are tired of horse-race-style reporting, and need to zoom out, I wanna tell you a story. It’s about an ancient force influencing the election. And, as a bonus, it’ll give you an Easter egg to watch for as the returns come in. THREAD
alan blount retweeted
COVID Update October 24: I spent the day reviewing data with & from the White House team in the spread of COVID-19.
The latest rush of new cases is very concerning. There are new insights as well. Will finish posting shortly.1/
alan blount retweeted
12 hour loop showing just how fast this fire exploded today because of wind. At Grand Lake now and heading into Rocky Mountain National Park.
#EastTroublesomeFire
12-hour loop of the #EastTroublesomeFire showing the rapid expansion of the fire and the insane wind-driven push it has made this evening towards Grand Lake and Rocky Mountain National Park.
alan blount retweeted
A research-backed strategy that reduces violence amongst police and military is making units 30% or more female. theatlantic.com/politics/arc… This strategy is so overlooked I don't know how $$$ helps. But happy to share more research, starting with Dr. Valerie Hudson's work.

































