It was shocking for AI, as it moved from niche to mainstream technology faster than ever before. But 2024 will be the year when this hype really becomes reality as people consider the capabilities and limitations of AI as a whole. Here are some ways we think that could happen.
OpenAI becomes a product company
After a management shake-up in November, OpenAI will be a different company — it may not look like it on the outside, but the trickle-down effect of Sam Altman taking more full charge will make all the difference. You can feel it on the level. And one of the ways we expect that to manifest is through the idea of “shipping.” You can see that in the GPT store. Originally he was scheduled for release in December, but was understandably delayed due to executive turmoil. “AI app store” will continue to be strongly promoted as a platform to get AI toys and tools. Don’t worry about Hugging Face or any other open source model. They have a great model called Apple and they follow it all the way to the bank. Expect to see more similar moves from OpenAI in 2024, as the prudence and academic reserve exhibited by previous boards gives way to unseemly greed for markets and customers. Other big companies working on AI will likely follow this trend (e.g. we expect Gemini/Bard to get into a ton of Google products), but I suspect it will be more pronounced in this case.
Agents, generated videos, and generated music graduate from quaint to experimental
Some niche applications of AI models, such as agent-based models and generative multimedia, will grow beyond “meh” status by 2024. If AI is going to help you do more than summarize things or create lists, it will need access to spreadsheets, ticket-buying interfaces, transit apps, and more. In 2023, several attempts were made with this “agent” approach, but none really caught on. I don’t expect anything to really take off in 2024 either, but I think agent-based models will look a little more convincing than they did last year. We’ll also see some clutch use cases that are notorious for tedious processes such as submission. Insurance claims. Video and audio will also find a niche where their shortcomings are less obvious. In the hands of skilled creators, the lack of photorealism will not be an issue and AI video will be used in fun and interesting ways. Similarly, generative music models are likely to be adopted by some major productions, such as games, where professional musicians can also leverage the tools to create endless soundtracks.
The limitations of monolithic LLM become clearer
So far, there’s been a lot of optimism about the capabilities of large-scale language models, and they’ve actually proven to be better than anyone expected, and can be used to create more computing power. As more are added, its capabilities further increase accordingly. But 2024 will be the year that something will be given. There is a lot of research going on at the forefront of this field, so it is impossible to predict exactly where this will happen. The seemingly magical “new” features of the LLM will be further studied and understood in 2024. Also, things like LLM not being able to multiply large numbers would make more sense. At the same time, the returns on number of parameters also start to decrease, and while training a 500 billion parameter model might technically yield better results, the compute required to do so could probably be more effectively deployed. may be. A single monolithic model is unwieldy and expensive, whereas a combination of multiple experts (a collection of smaller, more specific and perhaps multimodal models) is much easier to update in parts. However, it may prove to be nearly as effective.
Marketing meets reality
The simple fact is that it will be very difficult for companies to live up to the hype built in 2023. Marketing claims about machine learning systems that companies deploy to keep up will be subject to quarterly and annual reviews…and there is a strong possibility that they will be found to be inadequate. It is high. We expect significant customer withdrawal from AI tools as the benefits do not justify the costs and risks. At the other end of the spectrum, we may see litigation and regulatory action with AI service providers who are unable to substantiate their claims. Capabilities will continue to grow and advance, but it is not far off that all 2023 products will survive, and there will be a round of consolidation as the wave’s erratic riders decline and are consumed.
Source: techcrunch.com
