I find they are good for creative tasks. Picture and music generation, but also ideas - say, give me 10 possible character names for a devious butler in a 1930s murder mystery novel.
But yes, terrible for facts, even rudimentary ones. I get so many errors with this approach its effectively useless.
However, I can see on narrower training data, say genetics, this might be less of a problem.
There's a few ways they say it may help, this one seems the main one.
We foresee a future in which LLMs serve as forward-looking generative models of the scientific literature. LLMs can be part of larger systems that assist researchers in determining the best experiment to conduct next. One key step towards achieving this vision is demonstrating that LLMs can identify likely results. For this reason, BrainBench involved a binary choice between two possible results. LLMs excelled at this task, which brings us closer to systems that are practically useful. In the future, rather than simply selecting the most likely result for a study, LLMs can generate a set of possible results and judge how likely each is. Scientists may interactively use these future systems to guide the design of their experiments.
It’s only open source if the training data is and it probably isn’t, is it?
I don't know, though DeepSeek talk of theirs being "fully" open-source.
Part of the advantage of doing this (apart from helping bleed your rivals dry) is to get the benefit of others working on your model. So it makes sense to maximise openness and access.
I lived in Hong Kong for a few years. It has superlative public transport, and the (human) taxis were reasonably priced. However, as its so densely populated, I can only see cars getting so much traction. After a certain point the traffic jams are unavoidable.
I don't know the specifics. What seems more relevant to me is that lots of automakers around the world are getting to Level 4 by various, mostly similar ways.
Once you have Level 4 you have a viable robotaxi business model. Even if you stick to geo-fenced areas, and mapped routes, that covers 80%+ of urban taxi journeys.
The same holds true for buses and public transit. I'm very interested to see how efforts like this Level 4 mini-shuttle bus in France progress.
When robotaxis & mass transit like these are common, how many people will still want private cars?
Base fares start as low as 4 yuan (around 55 cents), compared with 18 yuan (around $2.48) for a taxi driven by a human
China is already the global leader in 21st century energy - dominating renewables, batteries, and EVs. Now it's poised to lead in robotic vehicles too.
Its robotaxis cost $30k, Waymo, who's been in the robotaxi game longer costs $150k. Combine this with the fact Baidu can offer fares that are just 20% of a human driver in China and still make money and you can see how the global demand for such vehicles could be in the hundreds of millions. Tariffs in Europe and America may slow things there, but it won't be the case for much of the rest of the world. Cheap Chinese robotaxis, with fares a fraction of today's human-driven journeys, will be ubiquitous all over the planet in the 2030s.
We rarely hear of the Chinese space program in western media, but it keeps doing interesting things. A recent launch tested an inflatable module for their space station. That was an idea that once seemed promising for the ISS, via Bigelow Aerospace, but never seemed to go anywhere.
This cargo mini-shuttle concept isn't new either. Thirty years ago an ESA version called Hermes got to the advanced planning stage before being scrapped. Some people have doubts that space planes, even launched with reusable rockets, are all that efficient, so it will be interesting to see how this fares.
I wonder what the monthly totals will be next year. When will it hit the 1 million mark, then 10 million?
The problem for all the investor funded AIs, is that data centers are huge costs. They're burning through billions of dollars every month. That makes sense if one of two of them emerge as dominant players who own most of the market share for future AI businesses.
If they all keep under-cutting each other by using open-source. It's more likely companies like OpenAI will crash and burn first.
Also, to me this means future self-driving transit will be commoditized.
If robotaxis can be as cheap as $10K, then their main cost per passenger journey will be the electricity to run them.
A lot of these open sourced AIs have been released that way to undercut competitors. Many people still think AI will consolidate into the hands only the biggest of Big Tech players, but it doesn't seem to be happening yet.
True. It's what keeps me optimistic. If we can get through the decay of the old world intact, there's a world of post-scarcity plenty ahead.