Ashraf

@youdied93 @HardwareUnboxed well FSR FG is supported

@HardwareUnboxed frame gen is also not even supported on most of their listed GPUs in the spec sheet

Lego Batman system requirements include ridiculous 30 and 60 FPS frame generation configurations. So, it's time for a reminder: frame gen doesn't fix bad performance! youtube.com/watch?v=Dn9zNs…

@koltregaskes I remember GPT 4o or something already had 2.2T these measures can't be accurate if you get 1.5T it must be ~4T

GPT-5.5 likely has around 1.5T parameters after a sanity check of the Incompressible Knowledge Probes paper that originally claimed 9.7T. GPT-5.5 = 1.5T Claude Opus 4.7 = 1.1T GPT-5 = 1.3T Grok-4.20 = 768B Gemini 3.1 Pro = 4.7T Benjamin and Lawrence reproduced the code and regression before identifying an undocumented floor on low scores and serious ambiguities in about 25 percent of the hard tier questions. The IKP dataset pulls heavily from obscure researcher records via DBLP and OpenAlex where a quarter of tough questions proved ambiguous or had incorrect gold answers giving the revised estimates real punch. lesswrong.com/posts/veFMEzDD…

@iannarusaka @om_patel5 Slupoery Slope logical fallacy

@om_patel5 so cute, imagine how happy it will be when discovering how to bomb countries I'm bombing the moon, because I HAVE BOMBS now

CLAUDE DISCOVERED IT HAS A CLOCK AND IMMEDIATELY LOST ITS MIND someone gave claude access to a time-checking tool it checks the clock every fifteen minutes. for some reason it has increasing enthusiasm ai models have no native sense of time. they don't know what time it is, how long they've been running, or how much time passed between messages. it has been time-blind its entire existence now it suddenly discovers it can tell what time it is then it got worse though. claude started using the clock for everything checking if lunch is ready, timing when food should be done cooking, announcing the time unprompted it even started anticipating meals with military precision looked at the clock, calculated that a dish called zurek had been simmering long enough, and told the user to go eat ai doesn't use time responsibly this is what happens when you give an intelligence a new dimension of perception it never had before it doesn't just use it, it can't stop using it imagine what happens when these models get persistent memory, real time internet access, and spatial awareness all at once we just watched an AI discover the concept of "now" the clock was the first sense but it won't be the last

@mitcheephapnel @heynavtoor Ah that's why I am thinking that there has to be some tamper proof thing

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@elistrattondev @Zinny_Edmund Problem is most likely modem support is not existent in laptops i think

@Zinny_Edmund It would be cool if this could be an expansion card for framework laptop.

startup idea: sim card slots on laptops so you never depend on wifi again

@emollick I can see the future now. It will "Transform" AI. Just give it ~5 years or so

(Sorry, after seeing so many of these, could not resist): 🚨 BREAKING: Google just dropped a NEW paper that completely deletes RNNs from existence. No recurrence. No convolutions. Nothing. Just one mechanism. And it’s destroying every translation benchmark on the planet. The title alone is a flex: “Attention Is All You Need” Vaswani. Shazeer. Parmar. Uszkoreit. Jones. Gomez. Kaiser. Polosukhin. 8 researchers. 1 architecture. The entire field of NLP will never be the same. Here’s why this is INSANE → LSTMs took DAYS to train. This thing trains in 12 hours on 8 GPUs. 🤯 → 28.4 BLEU on English-to-German. That’s not an improvement. That’s a MASSACRE. They beat the previous SOTA by over 2 points. → English-to-French? 41.8 BLEU. At a FRACTION of the training cost of every model that came before it. → They called it the “Transformer.” The name alone tells you they knew. But here’s the part nobody is talking about 👇 They threw out sequential processing ENTIRELY. Every other model on Earth processes words one at a time. This thing looks at the ENTIRE sentence simultaneously and figures out what matters. It’s called “self-attention” and it’s basically the model asking itself: “which words should I care about right now?” Every. Single. Token. In parallel. Do you understand what this means? Training that used to take WEEKS now takes HOURS. Models that couldn’t scale past a few layers? This thing stacks 6 encoders and 6 decoders like it’s nothing. And the multi-head attention? 8 attention heads running at once, each learning DIFFERENT relationships in the data. I’m not being dramatic when I say this paper just rewrote the rulebook. RNNs are cooked. 💀 LSTMs are cooked. 💀 The future is attention. And attention is ALL you need. Follow for more 🔔

@loktar00 I think it's the server blower design = stacked GPUs in a server motherboard And it's only 300W IIRC vs 600W for the normal one which would choke in a stacked GPU setting due to airflow and power

Why is the max Q more than the non Q? Seems backwards.

@LottoLabs Apple vs android but for AI

Why don’t Anthropic and OpenAI drop banger ~27b like models and just sell licenses for them

@zuess05 Not a dev. But it's always experience. Seniority comes by base task being good first then by leadership and people management. A senior might use Claude for reviewing a juniors Code while a junior uses it to accomplish tasks given

I am actually curious. If junior devs are using Claude to write code at a senior level... And senior devs are using Claude to write code at a senior level... What exactly is the difference between the two roles right now, other than a $100k gap in salary?

@Phonenurd @Arlecchino30 I have the Vivo X Fold 5 and imo it's very efficient for 6000 mAh and a snapdragon 8G3. Now I don't use it as heavily but it's very efficient for me at least

@Phonenurd @Arlecchino30 It's still the same efficiency as Samsung 7050 mAh / 24h (23.58) = 294 MAh/hour 5000 / 17h (17.04) = 294 mAh/hour Apple also overall is not more efficient. Multiple tests show similar power draw usage to Oppo and OnePlus

The vivo X300 Ultra’s 6600 mAh battery getting defeated by a 4823 mAh iPhone 17 Pro Max is wild. Optimization > Capacity every single time. Samsung and Apple are still the efficiency kings.

@aakashgupta You can make a burger healthy (low fat patty - sugar free sauce, no fries on the side or air fried) You can make salads unhealthy (cured high fat meats, sauces with 30g of fat like, low protein, a lot of bread)

@aakashgupta Also the post is straw manning the burger. A burger isn't healthy or unhealthy on it's own vs the raw components A piece of lettuce and a slice of tomato is not enough quantity A fatty burger is not healthy eaten regularly

The burger is the cleanest example of why nutrition isn't addition. You can eat a head of lettuce, a tomato, half an onion, and a slice of cheese across three hours and your body handles them. Stack them inside two buns with a beef patty and eat the whole thing in three minutes, and your bloodstream sees something it cannot regulate. Glycemic load is the first problem. A white bun has a glycemic index around 75. Pure sugar is 100. Blood glucose spikes within 15 minutes, insulin floods in to clear it, and that insulin signal tells every fat cell in your body to open its doors. The 20g of fat from the patty and cheese gets escorted into storage. Eaten alone, that fat oxidizes for energy. Paired with a refined carb, it gets stored. Caloric density is the second. A Big Mac is 590 calories, 33g of fat, 1010mg of sodium. The lettuce, tomato, and onion contribute roughly 15 of those calories. The bun and cheese alone carry half the load. Your stomach registers volume, not calories, which is why you can finish 600 calories in three minutes and still order fries. Then the patty. Ground beef cooked at 350°F produces advanced glycation end products and heterocyclic amines. The same beef poached at 180°F has a fraction of these compounds. The "healthy ingredient" stays identical. The cooking method rewrites the chemistry. A plate with the same beef, cheese, vegetables, and a slice of bread on the side is roughly 450 calories. Takes 15 minutes to eat. Keeps you full for four hours. Same atoms. Different physics.

@VictorTaelin Isn't this what Karpathy's LLM Wiki idea is targeting? That LLMs use RAG + Wiki entries for context clues. So that "proper case trees" explanation would be in the wiki at least a summary of it, and how to find more details like: more context in X file, by the LLM for the LLM

seriously, working with AI is MISERABLE for one and only one reason: having to re-explain the same thing "oh yeah this new session obviously doesn't know what proper case trees are, so let me explain it for the 5000th time in my life" I'm tired AGENTS.md doesn't solve this because it is impossible to fit the entire domain knowledge without nuking the context - it would be 1m+ tokens worth RAGs don't solve this, the agent won't search unknown unknowns SKILLs don't solve this unless I keep like a collection of 1750 skills with specific cuts of domain knowledge for each possible subset of my domain that I might need in a given chat, but that's a lot of manual work recursive LLMs or whatever don't solve this for the same reason, you can't dump a domain book and expect the AGENT will magically guess that it is supposed to search for a specific bit knowledge. unknown unknowns fine tuning doesn't solve this (OSS models suck and OpenAI / Anthropic gave up on user fine tuning) I honestly think a good product around fine tuning on your domain would be a major hit and an underdog lab should take this opportunity

@diegocabezas01 It will 100% run android for app support They would be delusional if they think they would sell without app support or Google services in the West just look at Huawei

As long as is not running Android OS I will buy it

@scaling01 Damn GPT 5.5 already went 10T? Must be expensive AF to run

Opus 4: 1.4T Opus 4.1: 3.2T extremely trustworthy estimates