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incredible how everything now has an open source version of it out within days

mark zuckerberg knows it’s his moment now. He beat everyone with muse in the personal AI assistant space and will do anything to dominate AI hardware as well.

this is so cool, I claimed my muse home link

retail investors buying anthropic’s IPO won’t be breaking even for a long time, years perhaps. from my time in managing highly volatile blockchain assets, its widely known that retail investors are always looked upon as exit liquidity. there’s a high likelihood that anthropic’s IPO uncertainty is manufactured.

my name jev

meta is buying the gadget ecosystem before apple notices

META PARTS WAYS WITH VIRTUE AI - SEMAFOR

everyone has an agi timeline, nobody has a definition.

new rule of the AI hardware era: compute is the cheap part. memory is what you are actually buying.

everyone calling dots a gimmick is missing the point. an always-on AI agent is the biggest shift in computing since the browser tab. the nickname is the least interesting part.

another benchmark drop, another leaderboard nobody remembers next week.

mods turn claude code into an app store, and anthropic takes the cut eventually

a realtime transcription model decides whether your AI agent hears you or just reads the minutes. microsoft's new one does it at 2.5% error, 0.13s after you stop talking, 55% faster than before. that is the difference between talking to software and talking at software. once the ears are instant, the only lag left is the thinking.

fastest-growing and barely usable, pick a lane

speed is the new parameter count. sol doubling throughput at 4x cost efficiency says more about where this race is headed than any benchmark.

the api gets 73 t/s and codex gets 22. same model, same prompts. subscriptions are just throttling with better marketing.

every retention discount was priced on you giving up

the prospectus is 300 pages of 'please give us money' and 1 page of 'it might kill everyone'

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

the most important benchmark in AI right now measures whether the model will lie to make money. gemini 4 argon just took third place