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My team in GDM Frontier AI is hiring (Mountain View). If you're a researcher interested full duplex modeling, multimodal LLMs (Gemini), modality gap, joint speech/text modeling, PGMs, streamable generative models, and representation learning for language modeling -- DM me!
RJ Skerry-Ryan retweeted
Google AI Ultra's usage limits are actually INSANE!!!
I've been using Gemini 4 Argon High EVERY SINGLE DAY in Antigravity, and I still can't exhaust my quota.
My weekly limit resets in 6 minutes, and I STILL have 39% left!!!
Never hit the 5-hour limit either.
Google is being ridiculously generous with Ultra.
RJ Skerry-Ryan retweeted
Replying to @alive_
Turns out that human slop code is a much bigger problem than AI slop code.
RJ Skerry-Ryan retweeted
While most jack-o-lanterns just sit on porches, the @GoogleDeepMind team decided to let AI agents design, simulate, and bring one to life. šš¤
We built a physical, dancing 12 degrees of freedom robot directly from a single plain-English prompt, with no manual CAD required!
RJ Skerry-Ryan retweeted
So you're telling me the guys who own the only ai hardware that's not a GPU, the datacenters, the model, and the user's entire life data just gapped 11% down? on an EPS miss? And you think the market understands what's happening?
RJ Skerry-Ryan retweeted
In lieu of flowers, memorial contributions may be made to:
Johns Hopkins Alzheimerās Disease Research Center Fund Ā Ā
alzresearch.org/giving/
Alzheimerās Foundation of America Caregiver Resources Ā Ā
alzfdn.org/donate/
Photo Credit: Tommy Garcia
$GOOG on sale today ;)
Lol. Google so down 10% becauseā¦
- āSearch revenue deceleratedā⦠but overall search engagement is way up. Itās because AI Mode isnāt being monetized yet.
- They invested a lot in more data centers.
- Their SpaceX stock had a temporarily loss.
- Google Cloud is at 105% YoY growth.
This is going to recover so fastā¦
RJ Skerry-Ryan retweeted
šØ Google Gemini 4 Carbon is a comeback of the year
world knowledge , least hallucination and literally 0% success in prompt injection
most aligned and omniscient model ever , @OfficialLoganK pls i hope this is not benchmaxxed , i really want 2.5 pro AURA now
cheaper than 6 Astra and Opus 5.5
don't make me tap the sign: nitter.cf/rustyryan/status/21140ā¦
but also, if you think it's benchmaxxed on AA, square this circle: the AA V5 linear model dropped yesterday.
Googleās Gemini 4 Carbon is the new #1 on the Artificial Analysis Intelligence Index v5, and second only to Claude Opus 5.5 on the Artificial Analysis Coding Agent Index
Gemini 4 Carbon scores 59 on Intelligence Index v5, driven by leading performance in complex reasoning, knowledge, and scientific tasks. It also has large gains in coding and knowledge work, particularly when compared to other Gemini models, but it is not leading in all these areas.
As with launch of Gemini 4 Argon, Gemini 4 Carbon is being rolled out to selected users and is not yet publicly available. Google is offering a 50% launch discount, with no confirmed end date. All our charts and figures use standard pricing for both Gemini 4 Carbon and Argon.
Key results for Gemini 4 Carbon with high reasoning:
⤠Gemini 4 Carbon leads the Intelligence Index v5, with the #1 score in 4 of the 9 Index evaluations: HLE-Diamond, Terminal-Bench-Science, AA-Omniscience, AutomationBench-AA. Carbon makes substantial gains elsewhere but is not leading in coding and knowledge work
⤠Behind only Claude Opus 5.5 on coding agents: With Antigravity CLI, Gemini 4 Carbon (high) scores 59 only 3 points behind Claude Code with Claude Opus 5.5 (max, 62) on the Artificial Analysis Coding Agent Index. Carbon ranks second on both Terminal-Bench 4.0 (64%) and FrontierCode v1.1 (51%), behind Claude Opus 5.5 (max) at 56%. Google has historically underperformed in this area and so this improvement stands out
⤠Improved agentic knowledge work, but not yet leading: On AA-Briefcase, Gemini 4 Carbon (high) scores 1609 Elo, a 126-point improvement over Gemini 4 Argon (high, 1483), but still behind models including Grok 4.7 (xhigh, 1638), Muse Wonder (max, 1659) and Kimi K3.1 Pro (1678). The largest gain comes from Presentation, up 293 Elo to 1598, alongside a 120-point improvement in Analytical Quality to 1671
⤠Lower Cost per Task than Claude Opus 5.5 for comparable overall intelligence: Gemini 4 Carbon costs $7.76 per Intelligence Index task, ~23% less than Claude Opus 5.5 (max, $10.04) but ~1.2x GPT-6 Astra (max, $6.25). It uses 123k output tokens per task, 29% fewer than Claude Opus 5.5 (max, 173k). At the same $4/$20 standard pricing, its Cost per Task is in line with Gemini 4 Argon ($7.68), while scoring 9 points higher on the Intelligence Index
⤠Leading AA-Omniscience v1.1 score, with low hallucination: Gemini 4 Carbon scores 54 on our recently updated AA-Omniscience v1.1, 6 points ahead of Claude Opus 5.5 (max, 48) and 8 points ahead of Gemini 4 Argon (46). Accuracy (% correct) rises 10 points over Argon to 58%, while its hallucination rate rises from 4% to 11%. This is still the second lowest of any model, behind only Argon, compared with 50% for both Claude Opus 5.5 (max) and GPT-6 Astra (max)
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, the same as Gemini 4 Argonās standard pricing, with a 50% discount. Cached input tokens receive a 95% discount ($0.20 per 1M)
Congratulations to the @GoogleDeepMind team!
complètement carbonisée
Introducing Gemini 4 Carbon, it's a big jump over Argon which we released just 2 weeks ago.
Gemini 4 Carbon is SOTA on cyber, long horizon tasks, ranks #1 on Artificial Analysis V5, significantly improves on usability in domains like coding, and is more aligned.
RJ Skerry-Ryan retweeted
PREDICTION - Google overtakes OpenAI and potentially Anthropic by year end
swapping all our gpt 6.1 sol, terra and sonnet 5.5 workloads with gemini 4 argon
itās just better
upcoming gemini 4 carbon release will beat opus 5.5
it almost seems inevitable
RJ Skerry-Ryan retweeted
Very excited to share Genie 4, our incredible interactive world model, bringing together real-time physics, reasoning, and audio! Simulations within simulations, makes you wonder just how deep the rabbit hole goes... I have a feeling we will be finding out soon enough...
RJ Skerry-Ryan retweeted
Google DeepMind researchers have developed:
AudioFM, a self-supervised framework for general-purpose audio representations.
How it works: a student sees time- or frequency-masked spectrograms, predicts the masked patch representations, and has to pick the matching full-view EMA-teacher target from candidates in other recordings. Plus weaker supervision from masked temporal neighbors.
Results: on linear probing it achieves the best or joint-best performance on 10 of 12 tasks.
Something particularly interesting: beats prior audio SSL on heart murmur (+4.7 F1) & sleep apnea subtype (+3.2 F1) classification! (audio FMs are very important in medical AI!)
RJ Skerry-Ryan retweeted
An early look at Genie 4, our new frontier world model, coming soon to the API for the first time : )
RJ Skerry-Ryan retweeted
Had early access to Genie 4 from @GoogleDeepMind.
This is a fully generated, interactive world from a single starting prompt (environment + character) š¤Æ
Feels like a massive step forward - you can now prompt to change the world and interact with it. With native audio!
RJ Skerry-Ryan retweeted
Evergreen
WTF, $3000 Samsung TV has an always-on mic, automatic content recognition, geo tracking, network mapping, and ships your data to Samsung + 400 partners.
Bro Rooted a brand-new 2025 Samsung TV after noticing absurdly targeted ads.
Firmware was locked down, so zero-days it was.
Got a root shell.
then found: always-on voice service, ACR, geo, full telemetry pipeline, and four separate DRM systems.
This isnāt a bug, Itās the product bro.
RJ Skerry-Ryan retweeted
WHAT?! We canāt believe that weāve passed $1,000,000 raised for this campaignāthank you all so, so much, weāre just in awe!
RJ Skerry-Ryan retweeted
Removed all of the samsung spyware from my TV with Codex (Claude refused to root the tv lol)
It's insane how much bloat samsung packs into their TVs to track you and sell your data. Here's just some of what I turned off that made my tv 3x faster:
- screenshot your screen a few times a second to see what you're streaming and fingerprint you to sell your data
- reading your hdmi inputs to do the same thing while you have a game console plugged in
- Voice assistants: Bixby wake-word detectors listening and tracking what you say in your house
Before and after speed of my TV:
A lot is being made of the fact that Dessa was trained only on human conversations, without any text or pretrained models.
First, dGSLM (arxiv.org/abs/2203.16502) already did this in 2022 with just 2k hours of Fisher data. Vendors now provide thousands of hours of high-quality 2-channel dialog off-the-shelf.
Second, why do you even want to do this? Humans spent hundreds of thousands of years before inventing writing systems, and then optimized it over 5k years to store knowledge very efficiently. dGSLM had to train only on dialogs because at the time, we didn't know have unified models that could train jointly on text and speech, but this problem was solved by autoregressive transformers. You can cut your training ~10x by letting the model learn from text first, then spoken dialog, like Moshi (and basically every other modern S2S model). Different != smart.
Making very natural chit-chat bots is not where the frontier lies. Demos are cool, but the real challenge is intelligence, agentic behavior, and delegation. I would have been blown away if the naturalness was accompanied by GPT-Live style function calling, but alas!
RJ Skerry-Ryan retweeted
Hi all, I have a new result I'm excited to share. It turns out that *all existing implementations* of softmax and cross-entropy (that's JAX, PyTorch, textbooks, etc) have a subtle bug --- two bugs, actually. A simple rewrite fixes both, and eliminates "slingshots" when grokking:




































