AI augmentation is a future requirement, but remain mindful of what’s outsourced. Going forward, we need more demanding journeys than we do mindless shortcuts. Shortcuts rarely yield fun, stories or lessons. If it's easy, it likely isn’t worthwhile.
For example, if you ask a model to “return all active users in the last 7 days” it might hallucinate a `is_active` column, join to an `activity` table that doesn’t exist, or potentially get the wrong date (especially in leap years!).
We previously talked to Shreya Rajpal at Guardrails AI, which also supports Text2SQL enforcement. Their approach was... See more
When you hear a phrase like a “7B parameter model,” 7 billion parameters is a measure of the dataset, not the model . You obviously couldn’t train such a model out of, say, a text of 50 words (well you could, but it would be highly informationally degenerate). And if you gave the training protocol 100 internets worth of data, 7B parameters may not... See more
AuthorityHacker surveyed 1,200 music consumers and got some striking results: 93% said they did not value AI-generated music as highly as music produced by humans. And, while over 60% said they would consider listening to AI music, some 56% also said they would not willingly pay for songs generated using AI. Perhaps most striking: 89% of those... See more
Subsequent research by Gerstgrasser and colleagues at Stanford and MIT (arXiv:2404.01413) provides important qualification: model collapse is not inevitable if synthetic data accumulates alongside real data rather than replacing it. The pathological scenario assumes complete substitution—thoughtful data curation can prevent the worst outcomes.
Novel technologies like artificial intelligence or neurotechnology are expected to have social implications in the future. As they are in the early stages of development, it is challenging to identify potential negative impacts that they might have on society. Typically, assessing these effects relies on experts, and while this is essential, there... See more