Large Language Models are not the be-all and end-all of Artificial Intelligence. At best they are regurgitators of accumulated human knowledge. The future of generative AI is at present unknown and probably unknowable. (think AI using AI to train AI)*
From Wired, June 20:
Anthropic’s latest Claude AI model pulls ahead of rivals from OpenAI and Google. But advances in machine intelligence have lately been more incremental than revolutionary.
When OpenAI announced GPT-4, its latest large language model, last March, it sent shockwaves through the tech world. It was clearly more capable than anything seen before at chatting, coding, and solving all sorts of thorny problems—including school homework.
Anthropic, a rival to OpenAI, announced today that it has made its own AI advance that will upgrade chatbots and other use cases. But although the new model is the world’s best by some measures, it’s more of a step forward than a big leap.
Anthropic’s new model, called Claude 3.5 Sonnet, is an upgrade to its existing Claude 3 family of AI models. It is more adept at solving math, coding, and logic problems as measured by commonly used benchmarks. Anthropic says it is also a lot faster, better understands nuances in language, and even has a better sense of humor.
That’s no doubt useful to people trying to build apps and services on top of Anthropic’s AI models. But the company’s news is also a reminder that the world is still waiting for another AI leap forward in AI akin to that delivered by GPT-4.
Expectation has been building for OpenAI to release a sequel called GPT-5 for more than a year now, and the company’s CEO, Sam Altman, has encouraged speculation that it will deliver another revolution in AI capabilities. GPT-4 cost more than $100 million to train, and GPT-5 is widely expected to be much larger and more expensive.Although OpenAI, Google, and other AI developers have released new models that out-do GPT-4, the world is still waiting for that next big leap. Progress in AI has lately become more incremental and more reliant on innovations in model design and training rather than brute-force scaling of model size and computation, as GPT-4 did.
Michael Gerstenhaber, head of product at Anthropic, says the company’s new Claude 3.5 Sonnet model is larger than its predecessor but draws much of its new competence from innovations in training. For example, the model was given feedback designed to improve its logical reasoning skills.
Anthropic says that Claude 3.5 Sonnet outscores the best models from OpenAI, Google, and Facebook in popular AI benchmarks including GPQA, a graduate-level test of expertise in biology, physics, and chemistry; MMLU, a test covering computer science, history, and other topics; and HumanEval, a measure of coding proficiency. The improvements are a matter of a few percentage points though........Gauging the rate of progress in AI using conventional benchmarks like those touted by Anthropic for Claude can be misleading. AI developers are strongly incentivized to design their creations to score highly in these benchmarks, and the data used for these standardized tests can be swept into their training data....
- Gartner: "3 Bold and Actionable Predictions for the Future of GenAI"
- Harvard on Digital: "The Future of Generative AI: Expert Insights and Predictions"
- MIT Technology Review: "These six questions will dictate the future of generative AI"
