The full 2027 edition of the rankings ' published by Quacquarelli Symonds, an organization specializing in education and study abroad ' can be found at TopUniversities.com. The QS rankings are based on factors including academic reputation, employer reputation, citations per faculty, student-to-faculty ratio, proportion of international faculty, and proportion of international students. The Institute received a No. 1 ranking in the following QS subject areas: Chemical Engineering; Civil and Structural Engineering; Computer Science and Information Systems; Data Science and Artificial Intelligence; Electrical and Electronic Engineering; Engineering and Technology; Linguistics; Materials Science; Mechanical, Aeronautical, and Manufacturing Engineering; Mathematics; Physics and Astronomy; and Statistics and Operational Research. MIT also placed second in seven subject areas: Architecture/Built Environment; History of Art; Biological Sciences; Economics and Econometrics; Marketing; Natural Sciences; and Statistics and Operational Research....

Eugenics, broadly defined, is the use of selective breeding to improve the human race. Most people imagine it as government control of reproduction intended to improve the population's genetics by encouraging reproduction by those with good genes, discouraging or banning reproduction by those with bad; what policies qualify depends on what you count as improvement. Getting parents more nearly the children they want is in my view a better definition of 'improvement' than giving them more nearly the children the government wants them to have. Getting parents the children they want, like getting other people what they want, is best done by leaving the choice up to them. If making it easier for parents to affect the genetics of their children seems to you an odd form of eugenics, consider the equivalent issue in economics. Some people imagine that the way to improve an economy is by having the government decide how much of what is produced and invested and how, but they are wrong, as demonstrated by the countries that tried it....

The AI boom has been built on a basic assumption: Bigger models are more powerful, and the most powerful models win. Now, the industry is about to learn what happens if that assumption starts to break. Mounting costs have already pressured users to give smaller and cheaper models a second look. This cost-conscious model-shopping is new and it's unclear how it will affect the industry, but the impact is likely to be significant. '[D]emand for intelligence is near infinite, but 80% of workloads will be running on 99% cheaper models within 12-18 months,' Armstrong wrote on X. '20% of workloads will still run on latest gen models where IQ maxing is important.' Before now, most AI companies have competed on quality, which has meant defaulting to the most advanced available model. If those same jobs can be handled by cheaper models without affecting quality, it would mean a massive shift in the economics of AI. And critically, much of the savings would be coming out of the pockets of the big labs, dealing a financial blow to OpenAI and Anthropic just as they're heading for their IPOs....

For more than a decade, customers spent their software budget procuring vertical SaaS products. ACVs, or annual contract values, were modest, customer acquisition cost had to stay below a ceiling, and the resulting go-to-market playbook was product-led growth, SDR-led and content-driven. With AI, many products are no longer SaaS but usage and outcomes based. They are replacing labor, not software. At my investment firm, Defy, we call this new category of companies vertical AI. Vertical AI spend doesn't just come from a customer's software budget. It often comes out of headcount as well, a much larger line item. As a result, ACVs have jumped meaningfully to 6- and 7-figure deals. I've written before about how AI opened up distribution for vertical SaaS, and how the value framing shifted from subscription pricing to labor substitution economics. As ACVs have grown in vertical AI, the go-to-market motion is changing too. We've explored tactics to drive a more efficient sales process. Direct sales has historically only worked at true enterprise scale. The cost of an AE's time wasn't warranted for smaller ACVs. Below a certain deal size, the math didn't work for high-touch sales. That's why SaaS GTM became PLG and SDR-led....