Our new pre-print on mesoscale image reconstruction from multiple views - termed - Rover-MRI. We reconstruct T2w image at an isotopic resolution of 180um in just 17 minutes of scan time. This work will be presented as oral at #ISMRM this year arxiv.org/abs/2502.08634

„It's not that I particularly enjoyed competing, but it had become an organic part of my life.” I can’t help to see this line describing current state of Academia really well. AI powered research has a chance to deliver so many results and what we call today „shortcuts”, that it actually may finally put an end to artificial rat race people do not enjoy but they are to involved to step out of. „My result” „My research” „My publication” - those are Corporate-Academia rewards, not original scientific intentions. You have to get many of those „my” things because that’s how you build your position in Academia. I can’t wait to see academic competition being replaced by an actual scientific cooperation. Many will oppose and chose to play the old game. The others will adapt and survive.

biorxiv.org/content/10.64898… Our preprint for rapid mesoscale dMRI — we use multiple rotating views (thick slices) and combine them to obtain high isotropic resolution dMRI data - going to 0.5mm. The time required for the scans is much less than existing methods - only about 40 mins (compared 80 mins using existing works)

Vought is increasingly isolated on medical science funding - on Appropriations, Uniform Grants Regulation, and the EO, he has been beaten back. Merit-based science backers need to go on offense, now: the forward funding & grant freezes at NIH need to stop, too.

Meritocracy isn't the problem. It's the solution. And the fact that both parties are now moving toward wholesale rejection of meritocracy spells the end of American innovation, freedom, and strength.

A great read by @dartmouth professor Dan Rockmore.

Any pursuit of superintelligence has to be grounded in the core principle that if the AI we build is not helping humanity and under human control, it's not worth pursuing. We also need to accelerate and spread the benefits of AI, such that they are diffused broadly across countries, communities, and companies. This requires a frontier ecosystem in which both closed and open-source models can thrive. And for firms, it’s imperative that they retain full control over their unique and tacit knowledge. Every organization should be able to build its own continuous learning loop/hill climbing machine, without becoming dependent on any one model provider, and have the ability to embed its own knowledge into models and weights they control. So, in this context, we welcome the research, focus, and deliberate pacing needed to get alignment right as the design goal. We also welcome ideas like "embedded evaluators" and the broader efforts to develop the mechanisms to make this more than just talk. The key is that this cannot be controlled by a handful of entities, but must have broad representation across the ecosystem, countries, and fields, including academia. This is the approach we are taking: broad access and choice at every layer of the AI stack; enterprise control of learning loops and models; and the “Code of Conduct” that underlies our own first party MAI models that we’ll publish tomorrow for public consultation.

A landmark moment for Gangwal School of Medical Sciences and Technology. We're proud to announce that Mr. Rakesh Gangwal (BT/ME/1975), Distinguished Alumnus, contributes an additional ₹300 crore towards the continued development of the @IITKMedSchool. This builds on his landmark ₹100 crore contribution in 2022, taking his cumulative support for the School to ₹400 crore. As part of this commitment, Mr. Gangwal will also match contributions up to ₹300 crore from other donors - inviting alumni, philanthropists, and well-wishers to join this vision of transforming healthcare through the convergence of medicine, technology, and innovation. The School's development includes a 500-bed super-speciality hospital and a proposed 200-bed cancer care research centre on the IIT Kanpur campus - bringing together doctors, researchers, engineers, and technologists to tackle tomorrow's healthcare challenges. "This additional contribution will help us bring this vision into reality sooner," said Prof. @agrawalmanindra, @Director_IITK, extending the Institute's sincere gratitude to Mr. Gangwal. We extend our deepest gratitude to Mr. Gangwal for his continued trust and generosity - and look forward to the impact this will create, not just for IIT Kanpur, but for healthcare innovation across India. Read More: iitk.ac.in/gsmst-rakesh-gang… #IITKanpur #GangwalSchool #RakeshGangwal #HealthcareInnovation #MedTech #Philanthropy #IITKanpurAlumni #GlobalImpact

Massive study published yesterday in @NatureHumBehav for anyone in the neuropsychiatry/mind-brain-behavior spaces Direct in vivo evidence for how attention can modulate the immune system in ways that seem almost unbelievable nature.com/articles/s41562-0…

AI based personas will increasingly be used as “friends” by people. These “virtual friends” will mostly agree with you and be your “ideal partner”. What will that do to real social and people to people interactions where disagreements are common ? Will it end up creating more conflicts and more “loneliness” or mental health problems ? Or will humans eventually will find a way out ?

Brilliant take on the actual reality by a greatly talented @shaurya_sinha7. Do watch it. You will be moved.

The contributions of the US to global science and engineering are tremendous, and on our 250th birthday we should celebrate and commit to maintaining the key role in our success of immigrants and international collaborations. @EricTopol @harvardmed

Yes I agree. I have 2 R01s as PI where my lab helps to coordinate a very productive multisite study (international study), and each R01 allocates 70k to me and my lab. Under the new rule, that would be it, and my lab would be 1 or 2 people. I think this will disincentivise collaboration. I am curious how they think a PI could coordinate a very productive consortium with this rule (asking for a friend ;)

University of California STEM professors want standardized tests back due to severe math deficiencies among students: “We now observe preparation gaps so severe that instructors must reteach middle school mathematics” “The current admissions metric, based primarily on GPA & essays, can no longer reliably distinguish readiness for university-level STEM majors in an era of severe grade inflation & AI assisted application essays”

AI is reshaping mathematical research. In @AmazonScience, @PennEngineers faculty and Amazon Scholars Michael Kearns and Aaron Roth describe how AI tools can generate formal proofs and accelerate discovery. Read more: bit.ly/4te2VFQ #AIandMath

Amazon just got caught running a secret price manipulation operation with Levi's, Home Depot, Walmart, and many more. Every time you "comparison shopped" online, you were looking at prices that were already rigged. Here's what happened: Amazon would monitor prices on Walmart, Target, Best Buy, Home Depot, and Chewy in real time. The second a competitor listed a product cheaper than Amazon, they'd contact the brand directly and tell them to "fix it." And the exact emails are now PUBLIC. Amazon sent Levi's links to two Walmart listings with the subject line "styles of concern." They basically said the prices on Walmart are too low and we have a problem. The next day, Levi's responded: "I talked to Walmart and they have partnered with us to take Easy Khaki Classic fit back up to ladder SPP price, $29.99 immediately." Levi's literally called Walmart and told them to raise the price. Because Amazon told Levi's to make the call. Walmart complied. Then Amazon matched the HIGHER price. Both retailers ended up charging more. The customer paid extra. Nobody competed. Same playbook with Hanes: Amazon sent them links showing Target and Walmart prices were lower. Hanes confirmed they "reached out to Target and Walmart to have the prices increased." Target increased the prices. Walmart increased the prices. Amazon kept their margins. But it gets even worse... Amazon told Allergan (the company that makes eye drops) that their product was "suppressed" on Amazon because it was cheaper on another site. Allergan responded: "Walmart got their price back up to $16.99." Amazon then unsuppressed the listing. They did this with pet treats on Chewy. Furniture on Home Depot. Products across dozens of categories spanning YEARS. The mechanism is simple but terrifying: If you're a brand and you sell cheaper on Walmart than on Amazon, Amazon suppresses your product, removes you from the Buy Box, buries you in search results, and effectively makes you invisible to 300 million customers. Brands can't afford that. So they call Walmart and Target and say "raise your prices or we'll lose our Amazon listings." Walmart and Target comply because they need the brand's products. Amazon captures 40 cents of every dollar spent online in America. That gives them the leverage to set prices across THE ENTIRE internet. Not just their own platform. So turns out, you were never comparison shopping. You were looking at a coordinated price floor set by Amazon through backroom phone calls between brands and their competitors. "Amazon is working to make your life more unaffordable." 3 separate antitrust trials are now scheduled for 2027. The FTC has its own case. 18 states plus the DOJ are piling on. This is literally happening during the WORST affordability crisis in a generation. Groceries up 25% since 2020. Housing unaffordable. Wages flat. And the largest ecommerce company on Earth has been secretly coordinating with brands to make sure you can't find a cheaper price ANYWHERE. "Competition" in retail is just a fantasy.

India runs one of the most unusual policy experiments in the world. Since 2014, any sufficiently large Indian company is legally required to spend a fixed share of its profits on social causes. Not just disclose it. Actually spend. No other major economy on earth does this.🧵👇

This week, the "AI replacing doctors" debate is back. The CEO of America's largest public hospital system says he's ready to replace radiologists with AI. The Stanford-Harvard NOHARM study shows top models outperforming generalists. The discourse is moving fast. I run AI at @UHN, the largest hospital in Canada. Here's what I actually see. We've developed AI models across imaging, pathology, and clinical decision support. In controlled conditions, the accuracy numbers are real. In some narrow tasks, models genuinely outperform. That's not hype. But the operational reality of running these systems inside a large hospital teaches you things benchmarks never will. The errors that hurt patients aren't the confident wrong answers. They're the quiet omissions, i.e., the thing the model didn't flag because it wasn't in the training distribution. NOHARM found 76.6% of AI errors were omissions. We see this too. And in a hospital, a missed finding doesn't just affect one case. It propagates: the downstream physician trusts the AI read, the patient waits, the window closes. The accountability structure also doesn't exist yet. When an AI-assisted diagnosis leads to harm, who is responsible: the physician, the hospital, the vendor? In Canada, we don't have a clear answer. No hospital system deploying AI at scale does. That's not a regulatory delay. That's a fundamental gap in the infrastructure for AI-in-medicine. What I'm genuinely optimistic about: AI is already changing how our radiologists work. Not replacing them, but changing the shape of the job. Routine reads get faster. Their time shifts toward complex cases, clinical correlation, cases where the AI flags uncertainty. That's the right direction. But "ready to replace radiologists" skips 10 hard years of work on deployment infrastructure, liability frameworks, clinician training, and failure mode monitoring that nobody wants to talk about because it's less exciting than accuracy benchmarks. The capability question is nearly answered. The deployment question has barely been asked. CEO story: beckershospitalreview.com/ra… NOHARM paper: arxiv.org/abs/2512.01241

Meditation ‘Works’ Faster Than Previously Thought | Psychology Today psychologytoday.com/us/blog/…

Indian & US partnership presents a chance to accelerate global good. With Priyamvada Natarajan (Yale) + Shivkumar Kalyanaraman (Anusandhan National Research Foundation), we talked the power of discovery & translation research, & the importance of innovation, at @IndiasporaForum.

Groups of agents don’t magically sort out the unreliability of individual agents. Instead, they often get stuck.