What to expect from AI in 2023
- But companies may still jockey for position in the most advantageous categories of upcoming laws, like the AI Act’s risk categories.The rule as currently written divides AI systems into one of four risk categories, each with varying requirements and levels of scrutiny.
- “However, despite being open-sourced, the best models are still inaccessible to a large number of researchers and practitioners due to their resource constraints.”Regulation like the EU’s AI Act may change how companies develop and deploy AI systems moving forward.
- Petals lets people contribute their compute power, similar to [email protected], to run large AI language models that would normally require an high-end GPU or server.Petals is creating a free, distributed network for running text-generating AI“Modern generative models are computationally expensive to train and run.
- Meanwhile, Highspot, whose AI-powered platform provides sales reps and marketers with real-time and data-driven recommendations, nabbed $248 million in January.Investors may well chase safer bets like automating analysis of customer complaints or generating sales leads, even if these aren’t as “sexy” as generative AI.
- Text-generating models have routinely been easily tricked into espousing offensive views or producing misleading content.Mike Cook, a member of the Knives and Paintbrushes open research group, agrees with Gahntz that generative AI will continue to prove a major — and problematic — force for change.
- “To make this commercially viable and accessible more widely, it will be important to address this.”Chandra points out, however, that that large labs will continue to have competitive advantages as long as the methods and data remain proprietary.
As a rather commercially successful author once wrote, the night is dark and full of terrors, the day bright and beautiful and full of hope. Its fitting imagery for AI, which like all tech has its [+11386 chars]