Konrad kording, @Penn Prof, deep learning, brains, #causality, rigor, neuromatch.io, c4r.io, Transdisciplinary optimist, Dad, Loves outdoors, 🦖

Philadelphia, PA
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What is interesting here is that AI does not produce value for *anyone* but AI companies. It just exploits aspects of the system. How much AI use is like this and how much produces genuine value? I would love to see an accounting.
🦔The Blue Cross Blue Shield Association says insurers paid out nearly $1 billion more than usual from AI-assisted hospital documentation in 2024-2025. Hospitals use AI to scan records and find secondary diagnoses that human reviewers missed. More diagnoses means higher reimbursements. But treatment levels haven't gone up. BCBSA's SVP of data science said AI is "identifying more billable conditions, not sicker patients." Insurers now deploy their own AI to deny those same claims. Patients pay for both through higher premiums. My Take This might be the most American healthcare story I've ever read. Hospitals bought AI to find more things to bill for. Insurers bought AI to deny those bills. The technology cost money on each end and the tab went straight to patients through higher premiums. A billion dollars moved and no one got any healthier. The only thing that changed was the size of the invoices. Two sides of a trillion-dollar industry found a new tool to fight over the same pool of money and the person in the hospital bed pays for all of it. Premiums go up, denials go up, and the AI vendors collect from everyone. If you want to know who AI works for, stop reading the press releases and look at where the money goes. In healthcare it went straight into the billing department. Hedgie🤗
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Replying to @philritz2
but can't DM you
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Replying to @GordonBrianR
can't DM you ;)
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I am writing a super accessible explainer of AI (for non-CS folks). Anyone wanna test drive?
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Kording Lab 🦖 retweeted
“Don't think for a second that because you are an alarmist that you are doing a social good.” This sentence is just devastating for so many intellectuals who need everybody to presume that they’re “the good people” Thank goodness we have Jensen!
Innovation Council
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Replying to @Maze_s_Center
Mark's criticism of carbon capture.
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Replying to @Maze_s_Center
Apparently the logic is faulty?
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Replying to @Maze_s_Center
As the price of electrical will plummet efficiency is a tad less crucial.
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Kording Lab 🦖 retweeted
See you next week in Philadelphia! 🎉 In just a few days, researchers and educators from around the world will come together for three days focused entirely on scientific rigor. We're excited for the talks, workshops, conversations, and games that happen when we bring our community together in the same room. Which part of C4R26 are you most excited about? See you at C4R26! 📅 September 28 📍 Philadelphia #C4R26
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Super excited about this. Hardware is where the future is at!
The reactor team at @terraformindies has demonstrated successful production of high purity methanol at scale at our Muroc desert test site. Let's review our progress in 2026. In January, we closed on our Muroc test site. By March, construction was underway. By May, we had 1.8 MW of solar installed. In July, we produced CO2 on site (nitter.net/CJHandmer/status/20801…), and in August, hydrogen (nitter.net/CJHandmer/status/20847…). Terraform Industries has built an incredible team to revolutionize not just one or two key technical pieces, but the entire stack required to convert sunlight and air into fuel. Like plants, only 100 times higher productivity per acre and requiring no irrigation, fertilizer, or pesticide. Two years ago, Terraform produced pipeline-grade natural gas for the first time. Since then, we've scaled up our methane reactor, increasing production by 250x and reducing contaminants by 10x, which allows us to increasing revenue per unit of product by 100x because it's now at chemically pure grade. But it was always clear to me that natural gas was only one piece of the puzzle. It is possible to convert natural gas into other hydrocarbon products like gasoline or jet fuel, but given our precursors are CO2 and hydrogen, we can do one better by directly synthesizing methanol as well. Methanol is far easier to convert into longer chain hydrocarbon products, either via the MeOH->DME->ethylene pathway, MTG, or via variations on Fischer-Tropsch. Methanol also has significantly higher revenue per molecule than pipeline natural gas, which forms an essential part of our cost-reduction-through-profitable-scale-up strategy, explained in more detail in our post: terraformindustries.wordpres… TL;DR: If our learning rate is above 11%, our margins will strictly increase as we scale up into a market worth about $10t/year. Not including induced demand. Amir joined the team earlier this year and speed ran the methanol reactor development program, successfully demonstrating recirculation and heat recycling before integrating these new technologies in a production scale reactor, built from the ground up at Terraform's facility in Burbank. As soon as the hydrogen team was done, we shipped our latest reactor up to the desert, plugged it in, and began activating the catalyst. An extended test campaign through the heat of summer followed, punctuated by bunnies nibbling on hoses! The hard work paid off, with Terraform's production of significant batches of high purity methanol, now packaged and ready to ship. A huge congratulation to the entire team, including Amir, Enric, Dominic, Hugo, and @lucie_nurdin. With the completion of this test, Terraform has now demonstrated TRL 9 operation of all of its subcomponents, each developed from scratch, in house, to deliver the highest possible value to the end customer. Terraform will never rest until we have broken the geological and geographical monopoly on oil, unlocking unconditional energy abundance for all of humanity. Join us!
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You are one of the key reasons I tell my doomer friends that engineering will solve climate change.
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Now lets be clear, they may also steal things that go beyond that but I think @OpenAI and @AnthropicAI have deeper knowledge about this.
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But in reality, the communications pattern that the user sees as explaining their idea had an original. RLHF removes it. Because users prefer to believe that its their idea and their clear communication. And science has no way of litigating.
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I find a weird thing with AI and attribution. It will credit the inventors of something. But it will almost never credit the source of an idea (that is short of having made it) or of a communications idea. And obviously scientists like that. The text is convincing. Logical.
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Replying to @Plinz @ArtDeza
Yeah I would even happily take a 20 to 1 bet (sorry)
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Probably dozens of millions if you ask me to at some level check all published papers where there is public data. There are also several business models. Short companies that invest in bad science. And whistleblower the NIH.
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Replying to @CJHandmer
We have done things like automatically check if images have been reused. Could be scaled to the internet. Requires $ million scale investment. Would probably improve science worldwide considerably. Similarly, recooking analyses for anything with existing data is well doable.
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This is cool. But why don't people know how to pour coffee? biorxiv.org/content/10.64898… the paper asks how to pour a coffee and the answer is "not like this!"
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If a mouse connectome was for sale. How much would you pay for it? Key metrics for you?
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Nice a paper quantifying my favorite rant. Where are your papers in this graph?
Causal overclaiming is widespread in the social sciences dlvr.it/TVGXCH
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