To finish the series: - Deterministic chain-seeded genetic computation.... We ran a chain-seeded genetic optimiser for 32 generations and proved every single step in zero-knowledge, then folded all 32 proofs into one. The whole lineage verifies on Kaspa in a single transaction, post-quantum. You can open the tx and check it yourself. What it is: a tiny program, an evolutionary search over a 16-value genome , that mutates and selects for a lower-cost circuit design, seeded by the Kaspa chain. Over 32 generations it drove its target circuit's scored constraint count down (best target ~72 → ~50; trending down, though it's a sawtooth it rotates through three circuit types). The part that matters: every one of those 32 steps ran inside a zero-knowledge VM and was proven correct a step that didn't compute correctly simply won't verify. Then all 32 step-proofs were folded into ONE. That proof is 222 KB exactly the size of a single step, and it stays that size no matter how many generations you add. (The catch, stated plainly: folding more generations costs the prover more time; only the final proof size is constant.) Kaspa verified the entire 32-generation lineage in one transaction: 7504fa32f74aa028301290299276a707cf98ffc2766b1be0daed4c5c41883f15. Flip a single byte of the proof and the network rejects it, we tried; it's rejected. And the verification path is post-quantum: hash-based the whole way (FRI/Poseidon2 + SHA-256), no elliptic curves or pairings anywhere nothing Shor's algorithm targets.* What this is and isn't: It's a feasibility experiment on testnet. It's deterministic, chain-seeded genetic computation not AI, not intelligence. We drive each step and proved a fixed lineage we chose; it does not yet run itself on-chain (that's the next build). The core, though, is real and checkable: a program's entire computational lineage 32 generations proven correct, post-quantum, verified by Kaspa in a single shot. *STARK security rests on hash assumptions plus the Fiat-Shamir heuristic, not on any pre-quantum hardness.show more

Kaspa Kii
20,730 просмотров • 2 месяцев назад
What a day! 🤯 Algorand was mentioned 32 times... by Google in its whitepaper on quantum risks, highlighting its leading work in PQC! Not sure everyone realizes how BIG this is, massive credibility for $ALGO and huge recognition for the team! 👏 Algorand has been one of the few blockchains/DLTs taking the quantum threat seriously for years, as it's not a question of if but when. Post-quantum implementation takes time and resources, it needs to be anticipated! The past few months have been incredible for $ALGO on that front, as it became one of the first major chains to execute a post-quantum transaction on mainnet using NIST-selected Falcon signatures! Not to mention the great news from a few days ago, with Chris Peikert officially joining Algorand Foundation from AT after the merge! So exciting, as Chris is literally one of the world's leading experts in post-quantum cryptography! What a chance for Algorand to have him and some of the best experts in PQC on its team! SO BULLISH 🔥🔥show more

Ⱥlex | france.algo 🇫🇷
25,162 просмотров • 5 месяцев назад
Elon Musk gave the entire entertainment industry its expiration... date, and he is the one building the thing that kills it. Musk: “My guess is that we see the first compelling half hour, pure AI show next year.” Next year. A complete show generated entirely by AI. No writers. No actors. No cameras. No sets. No crew. No studio. Just a prompt and enough compute to render a reality that never physically existed. And shows are the easy part. Musk: “I say probably we’re maybe three years away from AI does the whole video game.” A show plays the same way every time. A game has to generate a living world that reacts to every decision in real time across every single frame. That is a fundamentally harder class of problem. And Musk put three years on it. Right now a single AAA title takes seven years and half a billion dollars across thousands of engineers and artists just to ship it. Musk is describing a world where one person types a paragraph and gets something comparable. The entire value proposition of a multi-billion dollar industry lives inside that gap. And it closes in thirty-six months. But the prediction is not the story. The person making it is. This is not an analyst speculating from the sidelines. This is the man building the largest AI compute clusters on the planet. The man who built xAI from zero in under two years. The man stacking hundreds of thousands of GPUs into facilities designed to do exactly what he is describing. When Musk says three years, he is not guessing about what someone else might eventually ship. He is reading you a delivery date off his own roadmap. Every media company on Earth is valued on a single assumption. That quality content is expensive and difficult to produce at scale. That one assumption is the structural foundation underneath every studio, every network, and every publisher in existence. Musk is dismantling it with raw compute. The studios still parading thousand-person production teams are not demonstrating strength. They are advertising the exact cost structure that one person with a prompt and a GPU allocation is about to make irrelevant. And it does not stop at entertainment. If AI can generate an interactive world that responds to human input in real time, it can generate anything. Advertising. Architecture. Training simulations. Product design. Every industry built on humans manually constructing visual experiences frame by frame is sitting on the same countdown Musk just read out loud. Now zoom out. Because this is not just an industry story. For the entire history of human civilization, the distance between imagining a world and actually creating one required thousands of people, millions of hours, and billions of dollars. That distance built Hollywood. That distance built the gaming industry. That distance made content scarce and studios powerful. Musk is collapsing that distance to zero. When the gap between imagining something and it existing disappears, every business model built on the difficulty of creation disappears with it. That is not disruption. That is a full inversion of how human beings create. Musk did not make a casual prediction on that podcast. He told you what he is building. He told you the timeline. And he told you which industries do not survive it. The entertainment industry is still debating whether this future is real. Musk is not part of that debate. He is building. And he just told you the delivery date.show more

Dustin
22,458 просмотров • 1 месяц назад
Jeff Bezos just told you exactly how to price... AI. Nobody listened. Bezos: “AI is real and it is going to change every industry. In fact it’s a very unusual technology in that regard in that it’s a horizontal enabling layer.” Horizontal enabling layer. Three words that reprice the entire technology sector. The iPhone was a vertical. One product. One new market. Electricity was a horizontal. One substrate that rewired every market on Earth. Wall Street is pricing AI like it is the next iPhone. Bezos is telling you it is the next electrical grid. Right now, thousands of companies are trying to sell AI as a product. A feature. A tool. A subscription tier. Every single one of them will be priced to zero. You do not sell a horizontal layer. You do not compete with it. You build on top of it or you disappear beneath it. For a century, entire industries survived on one thing. Complexity. The friction of navigating law, medicine, logistics, finance. That was the moat. If you could not memorize the maze, you could not compete. A horizontal layer does not navigate the maze. It dissolves the walls. Electricity did not compete with the candle industry. It erased the need for one. The most dangerous part of a horizontal shift is how quiet it is. It moves underneath the economy. The surface looks normal. Revenue still holds. Every day you operate on the old substrate, you accumulate a debt you cannot see and cannot repay. The internet repriced distribution. AI is repricing cognition itself. When intelligence becomes a utility that runs through the walls of every company on Earth, the premium on human expertise does not erode. It evaporates. This is not a disruption. Disruptions replace products. This replaces the ground you are standing on.show more

Dustin
542,106 просмотров • 4 месяцев назад
Stop renting a chatbot and calling it your company’s... brain. Utopia is the first open-source enterprise world model I’ve seen that actually treats knowledge like a system, not a vibe. It's a Self-hosted, open source and built around the one question every other knowledge base ignores: when. Every fact in it carries a start date and an end date. Nothing gets overwritten. When something changes, the correction closes the old version and opens a new one. The history stays intact. So the graph isn't a snapshot anymore. It's a recording you can rewind. You drag a timeline on the screen and watch the whole thing redraw itself to show what was true on that date. Who owned what. What the policy said before it changed. All of it, replayable. And every fact points back to the exact sentence it came from. Nothing gets in without a receipt. Here's the part that got me. The whole thing is one binary and one Postgres database. That's it. No Elasticsearch, no separate vector service and no message queue. Most RAG stacks are six services duct-taped together. This is two. It even runs fully offline on an air-gapped network with any model you want.show more

Hasan Toor
172,771 просмотров • 6 дней назад
sorry, they just did WHAT someone gave a machine... one disease name, the leading cause of blindness in the developed world with 1.5 million americans already in its path, and it came back pointing at a drug that has sat in pharmacies for years under a different label: 551 papers read in 30 minutes against the 294 hours a human would have needed, and the loop that did it is public on GitHub most agent setups answer one question at a time, so the ceiling on the work is the quality of the question you happened to think of this one was handed a single question and wrote the second one itself. turns out that follow-up is where the real find was: a target called ABCA1, upregulated threefold, in an experiment no human ordered i read the whole paper looking for the trick, and the trick is structural. that is the second question, and it is the gap between an assistant and a factory: - hand the loop a field rather than a task: it was given a disease, and choosing the mechanism was part of its job - make it rank before it spends: 151 papers in, ten candidate mechanisms out, scored against each other before anything touched a bench - split reading from judging, so the agent that forms the theory is a different agent from the one grading it - close every cycle on physical reality: the verdict was an experiment, and another model's opinion was never allowed to stand in for one - feed each result back as the next question rather than a log line, which is the step almost nobody builds - search what already passed inspection first: the winner was an approved compound with a safety file already on record - write down what the round learned before opening the next one, so round two starts where round one stopped my read, and i think it is the uncomfortable one: reading was the entire bottleneck in that field, and everybody spent the decade optimising the writing. people ran every physical experiment here, the analysis agent needs a domain expert writing its prompts, and the authors decline to call this the leap it resembles. the thinking got replaced, and the hands did not so the question i cannot answer for my own setup: which step of your loop still stops dead until you sit down and type something bookmark this one. the four parts that turn one model into a line that runs like this, the queue, the rooms, the write permissions and the gate, are built file by file in the piece below ↓show more

Argona
32,475 просмотров • 1 месяц назад
A few points on the Powering Canada Strong announcement... that is important to understand; * Doubling Canada's electricity generation capacity is paramount. I just wish it wouldn't take 20+ years. We don't generate enough electricity to be self-sufficient or participate in future industries. We have no choice. Has to be done. It's something I called for a while and spoke on. * Linking the connectivity of Canada's fragmented grid. This is a must to increase productivity, and remove waste. It's a one step back for two steps forward type of investment. * the connection and expansion of the grid is one of the important things we need to do reach mining areas and develop these sectors and for the growth of smaller communities around. The problem with these whole announcement is that it is all net zero based which means it won't necessarily build the most reliable possible grid for the $ and will other ridiculous costs to be carbon tax trading based on the way. It's completely inefficient from capital planning point. Mark Carney says: It will require the spreading of costs over time using our AAA balance sheet so that ratepayers don't pay all of the costs of investments today. That means the government is planning to borrow MASSIVELY! That cost will appear not only in your electricity bill but also in the value of the CAD and interest costs that is already hitting record every single year. This plan is utilizing legitimate needed action to transform all of Canada's energy need into ideological driven carbon tax trade system and inefficient power generation that all together will cost Canadian taxpayers hundreds of billions more than it should.show more

Kirk Lubimov
24,482 просмотров • 3 месяцев назад
Stanford researchers did it again. They just built the... agent-native version of Git. When an agent works on a longer task, the run builds up a lot of state. This includes files edited/created, a dev server, a database, installed packages, KV cache, etc. Say the agent is at step 10 and makes a mistake, maybe it misreads a traceback and rewrites a file that was actually fine. The tests start failing, and the run goes off track, although everything through step eight was correct. By default, the agent just tries to fix it, which creates more edits and tool calls. This burns more tokens and grows the context. The other options are a person stepping in to redirect it or restarting the whole run from step one. That's wasteful, because it pays for every model/tool call again and re-prefills the context. Moreover, since an agent's run is non-deterministic, it doesn't reproduce the same early steps anyway. The reason it's hard to just jump back exactly to a previous correct step and resume from there is that the trajectory is only a message log. It records what the agent said and which tools it called, but not the live state underneath. That state includes things like memory, open file handles, child processes, installed packages, /tmp, and KV cache. None of that is in the log. Git can version the files, but it doesn't snapshot the running process or the KV cache. Checking out step eight moves the files back, but the process is still sitting in step-ten memory with a cold cache. Shepherd is a runtime layer by Stanford that records the run as a trace of typed events rather than a flat log. Each agent-environment interaction becomes a commit, similar to Git, but it tracks the live run. Its commit includes the agent process and the filesystem together, copy-on-write, so a branch carries the actual state and not just the files. Going back to a previous step is then a single call that forks from that commit and continues from the exact state. The copy-on-write fork is roughly five times faster than docker commit, and because the prompt prefix through step eight is unchanged, the KV cache is reused over 95% on replay, so early steps aren't reprocessed again. Once the run can be forked, a meta-agent can sit on top and operate it. It watches the trace and reverts as soon as it looks wrong, before the bad write is committed. In practice, it's just Python calling fork, replay, and revert on the trace, rather than a separate control plane wired into the harness. Not everything is reversible though. Files and sandbox changes undo themselves, but a database write has no automatic undo, so it needs a matching undo step set up in advance. Something external, like a sent email or a real charge, can't be undone, so the supervisor's job there is to catch it before it fires. They tested this on a few public benchmarks. On CooperBench, where two agents work on the same codebase, adding a live supervisor took the pair-coding pass rate from 28.8% to 54.7%. It's still early and labeled alpha. The benefit mostly shows up when a run gets branched a lot over a heavy sandbox state, which is exactly where restarting wastes the most tokens and time. If Git was made to make file changes reversible, Shepherd is trying to do the same thing for a live agent run. Shepherd Repo: (don't forget to star it ⭐ ) That said, Shepherd reverts a bad step inside a run. The harness around it, the prompts, tools, and checks the supervisor relies on, still drifts across runs as models and dependencies change. Akshay wrote about making that harness repair itself, where a failing trace gets diagnosed, the fix is verified against the exact input that failed, and the failure is locked as a regression test so it can't recur. Read it below.show more

Avi Chawla
441,570 просмотров • 2 месяцев назад
whoever leaked this has bigger balls than sense Google... Research and MIT ran the same agent jobs 260 different ways for Nature last month: they held the prompts, the tools and the compute budget identical and moved nothing but the wiring between the agents, and the same work swung from 70% worse than a single agent to 80.8% better, averaging out at 0.0% i ran my own single agent against the task list first and it cleared 6 of 10 alone, already past the line where a crew starts subtracting this is Graph Engineering, the layer that decides whether a crew is worth 80% more or 70% less, and it installs into the agent you already pay for: - score your solo agent on the real task first: above roughly 45% success that study predicts zero to negative returns from any crew you put around it - under that line, put one supervisor over the fan out: crews with no correction step amplified their own errors to 17.2x the single agent rate, supervised aggregation held it to 4.4x - give every worker one output and let none of them read a peer's draft, so a wrong step reaches the supervisor instead of four other agents - run the comparison again after every model upgrade, because a better model raises your baseline and a higher baseline is what makes a crew stop paying - keep the single agent alive as the control, the only number that says the wiring is earning its calls turns out the shape does not travel: the biggest win came off a finance task under one supervisor and the worst collapse off a planning task with independent agents my position, and it is the arguable one: a crew is a bet on your own diagram, and the model you pick moves that bet less than one arrow does bookmark this, the three moves that draw those arrows before you pay for one extra call are in the post below ↓show more

Argona
890,738 просмотров • 26 дней назад
Marc Andreessen just stripped artificial intelligence down to what... it’s really made of. Not the algorithms. Not the data centers. The raw material. Andreessen: “They’re literally made out of sand.” The most abundant, most overlooked substance on the planet. You walk on it. Build with it. Wash it off and forget it exists. Someone looked at that and saw a mind. The universe spent 13.8 billion years turning matter into consciousness. Carbon. Water. Amino acids. Eons of chemistry and selection pressure to produce a single thinking brain. We did it with sand. In under a century. Andreessen: “We light it up, and we put AI on it, and all of a sudden it’s thinking.” Biology was the first path matter found to become aware. Silicon is the second. The universe doesn’t care what material consciousness runs on. Only that the pattern is right. We just proved the pattern isn’t biological. Thought was never exclusive to flesh. Flesh was just the first material organized enough to produce it. Andreessen: “We’ve turned sand into thought.” The most profound thing about that sentence isn’t that we taught sand to think. It’s that sand was always able to. Every grain on every beach on Earth carried the capacity for thought. For billions of years. Waiting for something conscious enough to arrange it. Consciousness isn’t an accident that happened once on one rock. It’s what matter does when the pattern is right. The pattern is matter getting curious about itself. The universe isn’t dead matter with pockets of awareness. It’s dormant awareness we’ve only just started to wake. Every civilization that ever looked at the stars and wondered if it was alone was standing on the answer. We didn’t build a thinking machine. We proved the universe was always capable of thought. It just needed one species curious enough to rearrange the sand.show more

Dustin
20,829 просмотров • 1 месяц назад
We were taught the derivative as a formula to... memorise. A definition to recite. A rule to apply. Something that "gives you the slope." But nobody told us what the formula was actually saying. Every symbol is a sentence. Every fraction is a question. Every limit is a story about getting closer and closer to something you can never quite touch. The top of the fraction? That's a change. A difference. A before and after. The bottom? That's how long you waited to see it. The limit? That's you, zooming in, refusing to settle for an approximation - chasing the truth all the way down to an interval so small it almost disappears. Put it all together, and you get the most honest question in calculus: How fast is something changing - right now, in this exact instant? Not on average. Not over a minute. Not eventually. Right now. That's it. That's the derivative. It's not a trick. It's not a rule. It's a beautifully precise way of asking a very human question: what's happening, in this moment? We spent years solving these. Maybe it's time we actually understood them.show more

The Math Flow
22,498 просмотров • 3 месяцев назад
the first wave is closed. 125 wallets selected. identities... verified, the list is final. check yours now. selection was never a popularity contest. we optimized for one thing: honest hands. conviction, real understanding of what we build, no farmers. the first wave drew far more serious applications than 125 seats could hold. we read every single one, and cutting the list down meant turning away wallets that clearly understood talon and showed real conviction. the constraint was never the quality of the applicants. it was the size of the door. so we widen it, once. this is the last wave. wave two opens 75 seats, for the deserving the first cap could not hold. more honest hands also means a larger anonymity set, and a launch no single actor can bend. after this, the list is sealed for good. the token is close. when it moves, it moves fast. this is the last access before launch. it does not reopen. privacy is for everyone. the first hands are earned. ⬡show more

talon.
27,715 просмотров • 3 месяцев назад
clipping agencies rent offices now, $500,000 a year ten... editors, a manager, a lease, and the only thing any of them is paid for is noticing noticing is 310 lines of python, and i gave it away it runs on Robinhood Chain, so the clip pays whoever cut it CUT never sees a single frame of the stream. it reads chat, because chat knows before the editor does, before the dashboard does, before the streamer does [what those 310 lines do] 1. measure the last 10 seconds against that stream's own 5 minute baseline 2. never a global number, a big channel idling still beats a small one peaking 3. count how many people just typed clip it 4. call the clip api in the same second, not after the room reacts that last one is the whole thing. a twitch clip only keeps the 90 seconds before you hit the button, so if you noticed the moment yourself, you already lost it no key to read chat. it cannot post for you. it runs on your machine, not mine one command replays three minutes of recorded chat offline and fires a real moment on your screen, so you can watch it work before you trust itshow more

Carver
103,894 просмотров • 1 день назад
this is worth more than most five figure courses... 16 claude agents audit an entire repo at once, a second fleet re-checks every finding on fresh context, and the whole thing runs off one diagram instead of a prompt i ran it against my own code and got back 11 endpoints where i never checked who was logged in, 3 of which the verifier threw out before they ever reached me this is Graph Engineering, the layer above prompting, and it runs on the agent you already pay for: - write your plan out, then ask one question at every "and then": does the next step actually read what the previous one produced - the seams that fail that question were never dependencies, so those jobs run at the same time - the arrows that survive are your real edges, and the longest chain of them is your floor that no number of agents shortens - want it faster, cut a false edge instead of adding a worker - fan the independent work out, one agent per item, no shared state between them - send every finding to a separate agent on fresh context, because a model recognises its own writing 73.5% of the time and grades it kinder once it does - make that verifier check a real signal like a passing test, never the worker's own word that it finished - shard the fleet across worktrees so parallel workers stop overwriting each other, one rule frozen into every worker: never git stash, never git reset - merge only what came back verified, into one report instead of twenty open chats the catch is the ceiling. at 95% independent work 16 agents return 9.14x rather than the 16 you would guess, and even 256 only reach 18.6x, because the merge and the verify stay serial however wide you fan coordination itself is free plain code and every agent underneath it is billed, so start at twenty files and widen once it works bookmark this, the whole method with all six ready-to-run graphs is written out in the article ↓show more

Argona
157,245 просмотров • 1 месяц назад
Jeff Bezos just described AI in three words that... make most of the economy temporary. Bezos: “AI is real and it is going to change every industry. In fact it’s a very unusual technology in that regard in that it’s a horizontal enabling layer.” Horizontal enabling layer. Not a product. Not a platform. Not a feature. A layer. Underneath everything. Everyone is asking which AI company wins. Bezos is telling you that is the wrong question entirely. A horizontal layer does not produce winners. It produces a new floor. Everything standing on the old one either gets rebuilt or gets erased. This has happened exactly twice in modern history. Electricity. The internet. Both times the same pattern. The new layer appeared. The old economy kept running above it. Revenue held. Careers continued. Everything looked normal. Then quietly and permanently the entire structure reorganized around the new substrate. The people who did not move were not outcompeted. They were made structurally irrelevant. Not because they were wrong. Because the ground they stood on stopped being ground. Bezos is telling you it is happening a third time. Not with a product. Not with a platform. With intelligence itself becoming infrastructure. A horizontal layer does not compete with the expert. It makes expertise free. It hands a 22 year old with zero credentials the same cognitive output you spent a decade and a quarter million dollars learning to produce. For $20 a month. That is not disruption. Disruption replaces a product with a better product. This dissolves the scarcity your entire career was priced on. Not because the work disappeared. Because the wall around it did. Every profession that exists because knowledge is hard to acquire. Every company that profits because analysis takes time. Every industry that survives because complexity locks outsiders out. All of it rests on a single assumption. That cognition is scarce. AI does not challenge that assumption. It retires it. The people who understand this are already rebuilding. Quietly. Deliberately. While everyone else argues about whether the thing underneath them is real. Bezos did not give you a prediction. He gave you a position on a map. You are either above the new layer or beneath it.show more

Dustin
104,192 просмотров • 1 месяц назад
There is a room in Málaga that was built... to be the closest thing on earth to standing inside heaven. It is called the camarín of the Virgin of Victory, and it is hidden at the top of a tower inside the Santuario de la Victoria. To reach it, you climb and the ascent is the entire point... The building you are climbing through was completed in 1700, and it was designed as a single argument made in stone. At the bottom lies a crypt: a black chamber crowded with white plaster skeletons, a meditation on death and the brevity of life. From there a staircase rises, and as you climb it the light grows stronger and the imagery changes from bones to saints. The architects of the time understood this ascent as the soul's own journey, the dark crypt as the stage of penitence, the staircase as the stage of spiritual progress, and the room at the very top as the final stage: the union of the soul with the divine. That room at the top is the camarín, and its dome is one of the most extraordinary interiors in Spain... Every surface is covered in white and gold plasterwork. There is no empty space anywhere. The Baroque called this horror vacui, the horror of the void: the conviction that a space meant to represent heaven should not contain a single bare patch of stone. Out of that plasterwork emerge angels, flowers, birds, and mirrors. The mirrors are not decoration alone. They catch the light pouring in through the windows of the drum and throw it around the chamber, so that the gold seems to move and the whole room appears to shimmer and breathe. This wonder was built by people who believed that if you wanted to show a human being what heaven might feel like, you did not describe it to them. You built a room, and you let them climb into it... -- -- -- If you enjoyed this, I write a weekly newsletter read by over 50,000 people who love rediscovering the beauty of the past. You can join us here: If you'd like to support my work, a paid subscription is what makes it possible.show more

James Lucas
69,389 просмотров • 3 месяцев назад
What happens when Europeans find out how poor they... are? The Europoor? Nothing. That’s what happens. Americans ring the White House every morning to ask what the GDP is today, the way the rest of us check the weather. The trouble is that GDP is what you get when you stick Jeff Bezos and a man sleeping in a Walmart car park into a spreadsheet and take the average. It tells you the country is rich. It does not tell you that a hundred million people inside it are quietly not. GDP measures how much money sloshes around. It does not measure whether any of it ever reaches you, or what sort of life you get to live once it does. It also, rather conveniently, doesn’t mention the bill. Because the whole American miracle is being run on a credit card that has been on fire since the Reagan administration. The federal government owes nearly forty trillion dollars. The households owe another eighteen. Car loans, student loans, medical debt, a mortgage the size of a small principality, and a Visa bill that arrives in an envelope you have to open with tongs. This is the country lecturing the rest of us about prosperity. This is a man pulling up to valet parking in a leased Lamborghini and calling himself rich because nobody at the table has yet asked to see his bank statement. Run any household like that and the bailiffs would be through the door by Thursday. Run a country like that and apparently you get to be on the cover of The Economist. And this is where the whole sermon falls apart. Because on every single thing that actually makes a life worth getting out of bed for, Europe wins. Not by a bit. By a humiliating distance. The food. The streets. The holidays. The pavements you can walk on without being flattened by a Dodge the size of a small barn. The cities built before the invention of the strip mall. The Tuesday afternoon that contains an actual lunch, rather than a protein bar eaten standing up over a keyboard. The summer that contains an actual summer. Pick any parameter that matters to a human being who is alive and would like to remain so in reasonable spirits, and Europe is ahead. Often by a mile. Sometimes by an ocean. So no. Europeans are not about to find out how poor they are. We found out years ago, had a long hard look at the alternative, the debt, the diabetes, the drive-thru funerals, and decided we’d really rather not. If you like what you read, follow Gandalv on X: Gandalvshow more

Gandalv
226,018 просмотров • 4 месяцев назад
AI has had exactly two scaling axes that worked... so far, and the second one is starting to look finite too the first one was pretraining: with scaling parameters and data, we got world knowledge (i.e. ChatGPT had read enough to know things), but it started saturating a while ago the second one was RL, and people had been doing RL the whole time before that: RLHF is RL but it never scaled far because it was trying to control the exact output, which tokens come out, how the text reads, but you can only push that so far before you’re just polishing RLVR dropped that constraint: giving the model a task, then checking whether the final answer is right, and ignoring everything in between -- so the model does whatever it wants in the middle and only the endpoint gets graded, and that’s much closer to actual RL and it’s what bought us planning and reasoning (arguably, tool use sits around 2.5 on this list -- while useful, it's not a different kind of thing) so one axis gave knowledge, the other gave reasoning, and both of them are one model working alone the next axis is how many models you can get working on the same problem, which is a different kind of axis than the previous two we know that multi-agent RL has always been the harder problem: I spent years in that literature and the gap between single-agent and multi-agent is definitely not incremental -- it’s a whole different class of difficulty! which is also why the derivatives are steep at the start, nobody has picked the easy wins yet... and the thing that gates this multi-agent coordination is communication: models can only coordinate as well as they can exchange information, and right now they do that by writing sentences to each other imagine what could we possibly achieve if we properly open that third axis development by letting models to exchange information in their native "language" without loosing any computational data that they produce during inferenceshow more

Sasha Malysheva
12,177 просмотров • 28 дней назад
So, my opinion on what the Antarctic (Antarctica) Anomaly... is that it's a type of frequency technology. It must be way more powerful than HAARP, as many have claimed it to be, because we would see these anomalies at other HAARP sites, and we don't, not like this. With that said, and I'm very much trying to avoid letting what I want it to be not play a part here, I think it is a technology that is being used either off the coast of Antarctica itself or Bouvet Island. A third possibility is an area just to the northwest of the island that looks odd. It's possible it is a sonar scan from a ship, but why in that remote location? It looks like an antenna set up or rows of something that is out of place. I also believe that the weather events and fires that have taken place in Africa could possibly have been because of this. Each time we saw the anomaly, it was followed by a destructive weather event in Africa. A weird connection to that is we have been told and warned of a very busy 2024 Atlantic hurricane season. This is in part because of the above-average Atlantic ocean temperatures, which is the fuel to Hurricanes. With all this info, it's possible to see how the Anomaly could be a frequency tech that can manipulate or create weather, And or WARM up the Ocean temps to purposely enhance the Hurricane season and Storm growth. Keep in mind that many of our hurricanes and many of the biggest hurricanes have come from the west coast of Africa and form over the Cape Verde islands before heading towards the Caribbean and the United States. This is all of course speculation, and I'm learning many new things every day, so this idea may morph over time as we learn more. In the end, it is very hard to ignore all these findings. #antarctica #anonaly #AntarcticaAnomaly #BouvetIslandshow more

In2ThinAir
442,580 просмотров • 2 лет назад
this is more useful than my entire degree Elon... Musk's rocket company signed a $60,000,000,000 deal for Cursor in June, and eight days ago the two of them put a worker on sale for $200 a month: it gets its own computer in the cloud, signs into your accounts, clicks through your real apps, and hands back finished work instead of a draft for you to paste i ran one against my receipts folder on sunday and got back 14 filed, 2 it held because they needed a card number, and a saved method i never wrote myself Grok Bot is the one you train by doing your own job in front of it, and the whole handover fits in four messages tonight: 1. write out one job you did today the way you would brief a new hire: what has to be finished, which sites and files to work from, what to hand back, and where it stops and asks you 2. let it run once on something safe to get wrong, then correct the result until it is worth your name 3. say "save what we just did as a skill", and add the one rule about what always needs your approval 4. say "run that skill every weekday at 8 and post the result here. if the source is missing, tell me instead of using yesterday's numbers" xAI wrote that order into its own manual: one real job, then the saved method, then the clock. a schedule sitting on top of a method nobody checked replaces two hours of your clicking with two hours of your mistake turns out you never get to pick the brain, and that is the part i would argue about: the manual says there is no model picker for members or admins, no plan to add one, and the bill follows whichever model answered bookmark this, then open the piece below: which jobs deserve a worker of their own, and which ones quietly burn the seat ↓show more

Argona
21,946 просмотров • 20 дней назад
The main bronze door of Milan Cathedral weighs 37... tons and took a single sculptor 10 years to complete. The Duomo of Milan is one of the largest and most intricate cathedrals on earth, and its five bronze doors were built to be worthy of it. Every inch of the great central door is covered in sculpted bronze, dozens of scenes from the life of the Virgin Mary, faces caught mid-emotion, figures that seem to press forward out of the metal as if trying to step into the world... It was designed by the sculptor Ludovico Pogliaghi, who received the commission in the 1880s and did not see his door installed until 1906, having poured a decade of his life into modelling every figure by hand. And his was just the beginning. The five doors of the cathedral were not made together, or even in the same lifetime. They were created across nearly seventy years, by a succession of different sculptors, each carving their panels with the same obsessive care. The final door was not completed until 1965, its unveiling taken as the symbolic close of a cathedral that had been under construction, in one form or another, for 579 years... More than a century ago, the English polymath John Ruskin tried to put into words what it means to build something like this. He managed it in a single sentence. "When we build," he wrote, "let us think that we build for ever."show more

James Lucas
83,782 просмотров • 2 месяцев назад