@ValerioCapraro the fact that this needs to be DENIED just 5 years after LLMs hit public consciousness tells you how shocking the pace has been.
English
sl
1.4K posts
Finally, a big name has the courage to tell it: we are nowhere near AGI.
Demis Hassabis, CEO of Google DeepMind and Nobel laureate for AlphaFold, put it neat and clear:
"Today's systems are nowhere near [AGI]. Doesn't matter how many Erdős problems you solve… I think it's far, far from what a true invention, or someone like Ramanujan, would have been able to do."
This is the elephant in the room that many AI enthusiasts prefer not to see, or are actively trying to hide.
Erdős problems are well defined, often combinatorial, on finite spaces. They are exactly the kind of problems on which current AI can achieve spectacular performance with a lot of compute and knowledge.
A neural network can search a huge graph of possibilities. It can recombine existing knowledge at unprecedented scale. It can discover surprising solutions inside an already defined conceptual space.
But true invention is something else.
True invention is not only solving a problem.
It is inventing new objects, new dimensions, new connections. It is inventing new problems.
From resolving to inventing there is a discontinuity that we don't know how to bridge.
We are making extraordinary tools.
But we are nowhere close to AGI.
English
@kevinolearytv This entity is using money as a leverage to boost voices that actually exist and create a critical mass of dissent. People will line up to this agenda and this it is all their own idea. One such idea is "Billionaires BAD" Both the far right and left are well on their way to that
English
We uncovered something far bigger than I ever expected. After seeing coordinated false attacks against the Utah data center project, we brought in an advanced data science team to trace where the content was coming from and the results were shocking. What we found led back to organized networks, political activist groups, and funding trails tied to massive international entities. We dug through IRS 990 filings, tracked IP data from around the world, and uncovered what appears to be a coordinated campaign targeting energy and data center projects across multiple regions.
I shared 90 pages of evidence with federal law enforcement and raised concerns directly with contacts at the White House. This isn’t speculation. The filings, funding records, dates, and connections are documented. There’s a coordinated PR war happening around energy infrastructure and data centers, and we’re not going to ignore it.
English
@webisticsdawg @kevinolearytv did u watch it? He said Chinese communist party!
English
anthropic.com/news/chris-ola…
"We need informed critics who will tell the labs when we are failing. We need moral voices that the incentives cannot bend."
-Chris Olah
Which institution has EVER been truly immune to pride, ambition, geopolitical pressure and self-interest?
:(
English
@itskaveriirl It is definitely possible. Local models is the future, and welcome to using them. Me personally, I build several apps at incorporate local models, and I’m also fine-tuning them to fit my own workflow. It’s very powerful once you can figure out what you would like to do with them.
English
I just sequenced a human genome to 30× coverage entirely at home.
As far as I know, this is the first time this has been done.
I didn’t step foot in a lab once. Every step - from saliva collection, to running the sequencer - took place in a single room with a dining table + kitchenette.
Six weeks ago, I had never done wet lab biology before.
I used an Oxford Nanopore P2 Solo - the only commercially available sequencing device portable enough to do 30x human genome sequencing at home.
Biggest takeaway - I could build something that combined software, hardware, and molecular biology far faster than I thought was possible.
I can name >100 specific instances where AI helped me solve a technical problem that would previously have blocked me because I lacked access to a domain expert.
For example: how do I save my sequencing run when my DNA extraction yield is 4x lower than I need it to be, and I have this limited set of reagents to hand?
To make this work, I had to navigate multiple disciplines:
- writing software to monitor sequencing runs and orchestrate remote GPU infra for basecalling
- learning + executing 5 hour long molecular biology protocols
- building a hardware device to quantify DNA concentration
Apologies for the hyperbole, but I feel super lucky to be living in 2026.
A few weeks ago I decided to sequence a human genome to 30x at home.
Then I actually did it. And I did it really quickly.
English
@SethSHowes @antinertia this is amazing. It would be great if you could do a complete write up on exactly how you prompted claude, your thought process. I feel like we could all learn from people who use AI so effectively!
English
@elonmusk @olsenbdnr Some of us have brains that don't carry all the detail in our brains all the time. If I am in the middle of a problem I can tell you every miniscule detail. But once it is solved, the detail goes away and it becomes intuition. I guess I'll never work for Xai. cheering u on though
English
Evidence of exceptional ability and asking how they solved hard problems down to the brass tacks level is what matters.
Those who actually deserve credit know the details of the solution, because it was so hard it got seared into their brain. The phonies and posers who falsely claim credit will flounder at the second or third level of detail.
English
Conducted 2 technical interviews today. Reminded me how serious of a task this is.
You get to decide potentially the next n number of years the person you are interviewing within the span of 30 minutes or so.
I have nothing but hate towards those who conduct interviews without a care asking dumb leetcode hard questions they themselves couldn’t solve if the shoe was on the other foot.
English
Anthropic onboarding day: Michael Scott introducing Karpathy like he just signed Wemby in free agency.
English
@idahopatriot47 @elonmusk Good for you! But even as I support your absolute right to say that, my indoctrination is so strong that a part of me winced a little reading "beautiful white republican". We never see the white descriptor ever. It is usually unsaid. Usually see "beautiful < insert ethnicty/race>
English
@elonmusk I am unapologetically a beautiful white republican! I wake up every morning and thank God I’m not a liberal!!
English
@SenSanders New technology always raises the level of comfort for society and creates more jobs than it displaces.
e.g., Broom factory workers didn't all starve to death when vacuums hit the market.
English
Question for Musk: You tell us not to worry about the jobs that’ll be wiped out by AI & robotics because the government will provide everyone with “universal high income.” Really?
How will that be paid for when you can’t even support a 5% tax on your $817 billion in wealth?
English
@SenSanders Bernie, can you try and be a part of the solution? Elon has expressed a goal, which should make you happy. Instead of being confrontational, take him at his word and reach out to work out a solution that is not ideologically dogmatic
English
@IamTheKaz @BrianRoemmele Good luck in your venture! AI ethics is definitely evolving since we don't quite know the boundaries of its capabilities.
English
@sl80107 @BrianRoemmele Teaching kids how to properly use AI as a tool is a bit more timeless than that. I expect to teach what AI truly is, how it works and about AI ethics. I would more than likely cover some of the same things @BrianRoemmele does in his posts.
English
Thank you @BrianRoemmele for your take on this. I get so frustrated at the fear mongering and hate toward progress.
Brian Roemmele@BrianRoemmele
“THAT DATA CRNTER IS WASTING WATER, STOP ALL DATA CENTERS” I see, let’s talk about that t-shirt you are wearing first or the jeans, the water could support 100s of AI queries or days of computation. In the grand theater of human consumption, few spectacles rival the quiet hypocrisy of decrying data centers while embracing mountains of disposable clothing. Fast fashion: cheap, trend-driven garments churned out in endless cycles, represents a voracious, often invisible drain on water, energy, and ecosystems. Meanwhile, data centers, the engines powering AI and digital life, face scrutiny for their cooling needs. A clear-eyed comparison reveals misplaced priorities: the garment industry’s water use is vast, frequently consumptive or polluting in water-stressed regions, with products destined for landfills after minimal use. Data center water, by contrast, is largely local, often recyclable or evaporative (returning to the hydrological cycle), and supports immense economic and innovative value. It also is just a fraction of the garment industry. Water in the Garment Industry: Hidden Rivers and Polluted Legacies The fashion and textile sector consumes staggering volumes of water annually. Estimates range from 79 to 215 billion cubic meters (roughly 79–215 trillion liters), supplying the drinking needs of millions of people. This makes it one of the world’s most water-intensive industries, second only to agriculture in some assessments. Breaking it down garment by garment: • A single cotton T-shirt requires ~2,500–2,700 liters of water across its lifecycle (growing, processing, dyeing). • A pair of jeans: 7,500–10,000 liters. • Leather items push even higher (8,000+ liters for shoes).21 Cotton, which dominates natural fibers, is particularly thirsty. Global averages hover around 8,920 liters per kg of cotton lint (much from rainwater/“green” water, but ~2,344 liters/kg from irrigation/“blue” water in stressed areas like parts of India, Pakistan, and China). Processing and dyeing add 100–150 liters per kg of fabric, often with toxic chemicals. The dyeing phase alone accounts for hundreds of billions of liters yearly and contributes to ~20% of global industrial water pollution. Untreated wastewater laden with dyes, heavy metals, and chemicals flows into rivers, devastating local ecosystems and communities. Fast fashion amplifies this: Production has doubled in recent decades, with consumers buying 60% more clothes than 15–20 years ago, while usage duration drops. About 100 billion garments produced yearly; 92 million tonnes of textile waste generated, much ending in landfills (a garbage truck’s worth every second). In the U.S., landfills received 11.3 million tons of textiles in 2018. Synthetics (polyester ~55–68% of fibers) add microplastics via washing, now a major ocean pollutant. Cheap clothes are worn briefly, discarded, and replaced—embodying “take-make-waste” at planetary scale. This water is not local and often lost or ruined: Irrigation depletes aquifers in arid regions; polluted effluent renders water unusable downstream. The full supply chain spans continents—cotton from India/Uzbekistan, dyeing in Bangladesh/China, exporting environmental costs to vulnerable areas. Data Centers: Local, Cyclical Water Use for Digital Progress Data centers primarily use water for evaporative cooling (or increasingly air/closed-loop/immersion systems). Global estimates: ~560 billion liters annually now, potentially doubling or more by 2030 with AI growth: still a fraction of fashion’s footprint and far below agriculture (~70% of global freshwater). U.S. data centers consumed ~64 billion liters directly in 2023. BRAND NEW CLOTHING IS TOSSED IN THE DESERT WITH PRICE TAGS STILL ON IT. All to make the brand look rare. Can’t have poor folks wearing it. Meet the infamous fast fashion “clothing graveyard” (also called the “great fashion garbage patch”) in Chile’s Atacama Desert here: 1 of 3
English
@MazeLove14 you have not experienced Islamic extremism. I would suggest u do some more research. This is worlds apart. but yes religious craziness is bad all around
English
I took the longest break from DataExpert.io since I founded the company 3 years ago and nothing exploded!
For the last 17 days:
- no sales pushes
- no advertising
- no GitHub commits (my longest no commit streak since 2014)
- no sponsorships
Instead:
- saw 4 countries with my mom (Sweden, Finland, Norway, and Denmark)
- connected with my ancestors in Gørløse, Denmark
- deeply relaxed for the first time in many years
Sometimes taking a step back from your business is the only way to truly see your life in a more complete way!
English
@EcZachly some more of those mistakes. -Stay too long. -believe the corporate BS and NOT ASK for a salary bump. True story: once my boss said he could go back and ask for 5% more if I wanted. I said nah! when this product ships I will get that and more without having to ask. yup doh!
English
Most career decisions are made like France selling Louisiana.
In 1803, France was overwhelmed:
- wars everywhere
- short term pressure
- immediate cash needs
So Napoleon sold the Louisiana territory to the US for $15 million.
That’s about $450 million in today’s dollars.
At the time, it probably felt rational.
Fast forward to 2026:
The economy sitting on former Louisiana territory is now worth roughly $8 TRILLION annually.
If Louisiana Purchase territory were its own country, it would likely be the:
- 3rd largest economy on Earth
- larger than California
- more than double France’s economy
Cumulatively, that land has generated an estimated:
$250–300 TRILLION in economic activity.
That means the US has seen roughly a:
54,800,000% return on investment.
All because France optimized for the short term.
A lot of careers work the same way.
People:
- quit too early
- abandon compounding too soon
- optimize for immediate salary bumps
- underestimate skill accumulation
- underestimate network effects
- underestimate geographic leverage
The hardest part about long-term bets is they usually look stupid for years before they look obvious.
One good “Louisiana Purchase” decision in your career can change your entire financial trajectory.
Your:
- location
- skill stack
- network
- distribution
- industry choice
can compound for decades.
What’s the “Louisiana Purchase” bet you’re trying to make in 2026?
English
@KevinNaughtonJr I have a theory, can some HR person in the know confirm this? I think they estimate a percentage of the remaining employees will quit after being demoralized and overwork due to layoffs. So they don't have to pay severance.
English
when google did layoffs a few years ago tons of people found out they were laid off because they couldn't badge in after commuting to the office
multiple people on my team and neighboring teams were affected by the layoffs but the crazy thing is i know people who were rehired within a few months of being let go
i think companies just have a large margin of error when they do these things. they figure the handful of people they incorrectly lay off will pale in comparison to the cost savings they reap by removing a large percentage of the workforce
these layoffs feel so dystopian nowadays especially since meta employees ended up learning the exact day the massive cuts would happen
imagine having to do your job the last few weeks knowing that thousands of people were going to be laid off by the end of the month
i actually don't think these layoffs should surprise people since businesses will always do what's best for business and it's best to accept that notion when you join any company
never be loyal to a company because a company will never be loyal to you
you have a 9+ digit employee number at these companies for a reason because you're literally just a number
these companies don't owe you anything and this should feel freeing since it should make you realize you don't owe them anything either
don't feel bad about quitting
don't feel bad about taking vacation
don't feel bad about signing off early
employees should min-max employment the same way companies min-max employees
Zach Wilson@EcZachly
Meta reached to interview me for a principal role the same week they decided to layoff 8,000 people! I’m sure there was at least 1 out of those 8,000 people who got let go who would’ve been a good fit for the role they wanted to hire me for. A few of my staff engineer friends got let go so I know this is true. Instead they: - axe everybody - treat them like a cost - rehire where there’s pain What ever happened to employee retention? Why do companies expect us to be loyal to them if they don’t even try to retain us when they have hundreds of billions of dollars? It would be cheaper financially for them to retain one of those 8,000 people. It would be cheaper emotionally for the people who got let go too How do these big tech companies expect people to put their blood, sweat and tears into work while also saying, “yeah we’ll cut you at any moment.” I don’t know. The culture around AI and layoffs has gotten unbelievably toxic
English
@KevinNaughtonJr this. do the job you are paid to do. Give it 100%. not a second more. But if ur contract includes escalations for more work, then by all means do the work you are compensated for.
English