weekend ai reads for 2024-04-19

Whether you’re a seasoned user or just starting your AI journey, this cheat sheet should serve as a pocket dictionary for many areas of communication with large language models.

One of the key advantages of SLMs is their suitability for specific applications. Because they have a more focused scope and require less data, they can be fine-tuned for particular domains or tasks more easily than large, general-purpose models.

I think vector databases / RAG are really meant for Search. And only search. Not search as in “oh – retrieving chunks is kind of like search, so it’ll work!”, real google-and-bing search.

CRAXIS n. the unease of knowing how quickly your circumstances could change on you—that no matter how carefully you shape your life into what you want it to be, the whole thing could be overturned in an instant, with little more than a single word, a single step, a phone call out of the blue, and by the end of next week you might already be looking back on this morning as if it were a million years ago, a poignant last hurrah of normal life.

AI can be kind of useful, but I'm not sure that a “kind of useful” tool justifies the harm.

According to Altman, startups currently have two choices: They can either assume that models won't get better and build products on current versions.

Or they can count on OpenAI to keep developing the models at the current rapid pace, making them much more powerful with each update.Altman says 95% of startups should choose the second strategy. But so far, many have taken the first approach.

Because each student has their own chatbot to ask their own questions, their learning experience is personalized. Their critical thinking skills are sharpened. Instead of being something educators are afraid of, Shelton says they can start teaching kids how to use it to make the kids feel invested in what they’re learning.

PowerBuddy is designed to deliver adaptable, individualized experiences enabling educators, students, administrators, parents, and communities to unlock the untapped potential of personalized teaching and learning, paving the way for a future where every student can thrive as lifelong learners.

The increasing use of synthetic data in aligning AI models (e.g., Constitutional AI) can introduce significant ambiguity and uncertainty. The goal of AI alignment is to ensure that AI systems behave in ways that are aligned with human values and intentions. However, synthetic data, which is artificially generated rather than collected from real-world sources, may not accurately represent the nuances and complexities of human values and preferences. This discrepancy can lead to AI models learning from data that is biased, ungrounded, or misrepresentative of real-world scenarios.

According to IBM, the feature processes data about all the shots on the course by all competitors over all four rounds in the last eight years — that’s 170,000 total shots, to be precise — to calculate the overall probabilities of what’s going to happen next “based on the resting positions of the ball relative to the next shot,” as Noah Syken, vice president of sports and entertainment at IBM, put it.