I'm hoping their example is just the surface level and the technology is much richer. I'm very interested to see how they're adding:
- real-time data to LLM retrieval
- validation of recommendations (hallucination reduction)
- enriched metadata for recommendations
When you consider the most recent Godzilla film, Minus One, is the 37th in that franchise, and was not only nominated for an Oscar, and may be it's most lucrative, you can see why Toho would aggressively police that copyright.
It's not true. Carbon emissions are record high and growing. I think I read that carbon emissions in the US declined somewhat this year. I also read (small sliver of hope) that we have avoided (so far) the worst-case climate scenario.
The US is also producing a record amount of oil (locked-in emissions), Biden just approved some huge drilling lease and they're considering allowing construction of new LNG terminals in the Gulf. :-\
Duolingo was one of the first companies to partner with OpenAI on leveraging their language models. I think they were using GPT-3 before ChatGPT was even popularized.
Generally agreed. I think 4-5 data points is fine, but the advantage of pie charts is that it's a quick visual representation of what proportion of the 100% can be attributed to the 4-5 segments.
Pie charts fail again once the distribution is very skewed (1 segment = 99% and the other 3 shared 1%). It also fails when the distribution is too even (5 segments 20% each). They shine the most when there is variance, but overall easy to interpret the distribution differences.