NYTimes: “One hypothesis for how large language models such as o1 think is that they use what logicians call abduction, or abductive reasoning. Deduction is reasoning from general laws to specific conclusions. Induction is the opposite, reasoning from the specific to the general. Abduction isn’t as well known, but it’s common in daily life, not to mention possibly inside A.I. It’s inferring the most likely explanation for a given observation. Unlike deduction, which is a straightforward procedure, and induction, which can be purely statistical, abduction requires creativity…Large language models generate sentences one word at a time based on their estimates of probability. Their designers can make the models more creative by having them choose not the most probable next word but, say, the fifth- or 10th-most probable next word. That’s called raising the temperature of the model. One hypothesis for why the models sometimes hallucinate is that their temperature is set too high.”
FT: “Once known as a producer of everything from washing machines to chips, Hitachi has slimmed down, with a primary focus on digitising infrastructure and power grids…From the outside, Hitachi still looks like a sprawling conglomerate spread across train infrastructure, power grids and factory automation. But investors are convinced it has successfully broken conglomerate silos, applying IT and data science to become something like a management consultant to utilities, manufacturers and railway operators.”
Arm CEO Rene Haas: “At our core, we are computer architecture. That’s what we do. We have great products. Our CPUs are wonderful, our GPUs are wonderful, but our products are nothing without software. The software is what makes our engine go. If you are defining a computer architecture and you’re building the future of computing, one of the things you need to be very mindful of is that link between hardware and software. You need to understand where the trade-offs are being made, where the optimizations are being made, and what are the ultimate benefits to consumers from a chip that has that type of integration. That is easier to do if you’re building something than if you’re licensing IP. This is from the standpoint where if you’re building something, you’re much closer to that interlock and you have a much better perspective in terms of the design trade-offs to make.”
Sajith Pai: “I have been looking for a term, an acronym or a phrase that describes these families who speak English predominantly at home. These constitute an influential demographic, or rather a psychographic, in India – affluent, urban, highly educated, usually in intercaste or inter-religious unions. I propose to call them Indo-Anglians. Unlike Anglo-Indians, the original English-speaking community in India, who were Christians, Indo-Anglians comprise all religions, though Hindus dominate. Indo-Anglians are also a highly urban lot; concentrated in the top 7 large cities of India (Mumbai, Delhi, Bangalore, Chennai, Pune, Hyderabad and Kolkata) with a smattering across the smaller towns in the hills and in Goa.”
WSJ: “The outsize success of America’s talented entrepreneurs doesn’t stem from their superior intelligence. It comes from working at companies such as Google and Microsoft, which mine the technological frontier and expose employees to valuable knowledge, insights and opportunities. Apple is worth more than the 30 largest German companies combined. Apple’s employees and its alumni use their knowledge and training to create more value than their counterparts in Europe. Unlike Europe, the enormous success of American entrepreneurs motivated an army of talented Americans to get valuable on-the-job training, work longer hours, take risks and succeed. A small amount of success bubbles up from a large pool of failure.”
