AI Top-of-Mind for 9.13.24 — OpenAI Chat o1-preview (aka Strawberry)
Today: OpenAI Chat o1-preview, McKinsey tech trends, Flux AI image generation, where AI generated writing fails, and novel approaches to elderly care
Top-of-mind is the release by OpenAI if ‘Chat o1-preview,’ aka Strawberry. From the OpenAI site:
· We’ve developed a new series of AI models designed to spend more time thinking before they respond. They can reason through complex tasks and solve harder problems than previous models in science, coding, and math.
· In our tests, the next model update performs similarly to PhD students on challenging benchmark tasks in physics, chemistry, and biology. We also found that it excels in math and coding. In a qualifying exam for the International Mathematics Olympiad (IMO), GPT-4o correctly solved only 13% of problems, while the reasoning model scored 83%. Their coding abilities were evaluated in contests and reached the 89th percentile in Codeforces competitions. You can read more about this in our technical research post.
· Both o1-preview and o1-mini can be selected manually in the model picker, and at launch, weekly rate limits will be 30 messages for o1-preview and 50 for o1-mini. We are working to increase those rates and enable ChatGPT to automatically choose the right model for a given prompt.
And from McKinsey, an update on latest technology trends, including, you got it, Gen AI. Some good background reading including topics such as robotics and quantum.
Next, what is ‘Flux AI’ and what can it do? Jim Clyde Monge dives into the tool how to use it to generate an unlimited number of personalized images.
Also on the tools front, but a bit more negative, is the use of bots for writing and when it backfires. Desiree Peralta penning at ‘Practice in Public’ looks at the complexity that AI adds to text generation, with the following example:
Paragraphs like this one:
· “Luckily, the heavy rain had stopped, and only small clouds remained in the sky. They had evacuated us all to the parking lot because of a gas leak in the kitchen, and the medical staff began moving some patients to other buildings.”
Were converted into this one:
· “The deluge had ceased, leaving behind a dampened calm as we congregated in the parking lot, driven out by the emergency sirens blaring from the hospital’s speakers. A hazardous gas leak in the kitchen had prompted the evacuation, prompting a flurry of activity among the medical personnel as they orchestrated the relocation of patients to safer quarters.”
Finally, more help for the elderly, as Mary Ara writing in ‘AI Advances’ describes a Python tool to read prescription bottle labels, a challenge for many of the elderly or sight impaired. A good example of the many new approaches to care that AI enables.
Link to output: https://aramary.com/images/projects/output.mp4
