• Promised adult mode - now shelved.
• Launched Sora video generator, landed Disney deal - ended Sora 100 days later.
• Announced Stargate project - cancelled one year later.
• Altman once called Al + ads a "last resort" - 16 months later launched ads.
• Launched in-app shopping with direct checkout - now cancelled.
• Promised first hardware device this year - now delayed to 2027 per court filings.

The only things they still have left are a chatbot (Gemini and Grok are on the path to beat ChatGPT there) and a coding tool (Anthropic is already beating OpenAI there). So after both ChatGPT and Codex slide into irrelevance, nothing will be left. How soon does it happen, what's your bet?

Link to the article: https://www.theatlantic.com/technology/2026/03/sora-openai-identity-crisis/686544/

After seeing all the hype about o1 Pro's release, I decided to do an extensive comparison. The results were surprising, and I wanted to share my findings with the community.

Testing Methodology I ran both models through identical scenarios, focusing on real-world applications rather than just benchmarks. Each test was repeated multiple times to ensure consistency.

Key Findings

1. Complex Reasoning * Winner: o1 Pro (but the margin is smaller than you'd expect) * Takes 20-30 seconds longer for responses * Claude Sonnet 3.5 achieves 90% accuracy in significantly less time
2. Code Generation * Winner: Claude Sonnet 3.5 * Cleaner, more maintainable code * Better documentation * o1 Pro tends to overengineer solutions
3. Advanced Mathematics * Winner: o1 Pro * Excels at PhD-level problems * Claude Sonnet 3.5 handles 95% of practical math tasks perfectly
4. Vision Analysis * Winner: o1 Pro * Detailed image interpretation * Claude Sonnet 3.5 doesn't have advanced vision capabilities yet
5. Scientific Reasoning * Tie * o1 Pro: deeper analysis * Claude Sonnet 3.5: clearer explanations

Value Proposition Breakdown

o1 Pro ($200/month): * Superior at PhD-level tasks * Vision capabilities * Deeper reasoning * That extra 5-10% accuracy in complex tasks

Claude Sonnet 3.5 ($20/month): * Faster responses * More consistent performance * Superior coding assistance * Handles 90-95% of tasks just as well

Interesting Observations * The response time difference is noticeable - o1 Pro often takes 20-30 seconds to "think" * Claude Sonnet 3.5's coding abilities are surprisingly superior * The price-to-performance ratio heavily favors Claude Sonnet 3.5 for most use cases

Should You Pay 10x More?

For most users, probably not. Here's why:

1. The performance gap isn't nearly as wide as the price difference
2. Claude Sonnet 3.5 handles most practical tasks exceptionally well
3. The extra capabilities of o1 Pro are mainly beneficial for specialized academic or research work

Who Should Use Each Model?

Choose o1 Pro if: * You need vision capabilities * You work with PhD-level mathematical/scientific content * That extra 5-10% accuracy is crucial for your work * Budget isn't a primary concern

Choose Claude Sonnet 3.5 if: * You need reliable, fast responses * You do a lot of coding * You want the best value for money * You need clear, practical solutions

Unless you specifically need vision capabilities or that extra 5-10% accuracy for specialized tasks, Claude Sonnet 3.5 at $20/month provides better value for most users than o1 Pro at $200/month.

Link: https://www.theguardian.com/lifeandstyle/ng-interactive/2026/feb/13/openai-chatbot-gpt4o-valentines-day

OpenAI says it started training a new internal model on August 28.
That was just 24 days ago.
Since then, the model has reportedly solved 100+ long-standing open problems in mathematics across multiple fields on top of its recently announced work on the Navier–Stokes Millennium Prize Problem.
And apparently, even OpenAI’s own mathematicians are surprised by the pace.
But here’s the part that really caught my attention:
The problem may no longer be “Can AI solve difficult mathematics?”
It may be:
“What do we do when AI starts producing too much new mathematics for humans to evaluate?”
An independent advisory group involving mathematicians such as Edward Witten, Timothy Gowers, and Martin Hairer has reportedly been formed to help assess the significance of these results and coordinate their release to the mathematical community.
The group’s immediate challenge?
The “large number of significant results” reportedly being generated by the model.
Of course, these claims still need rigorous, independent verification. Mathematics doesn’t accept impressive demos proofs have to survive expert scrutiny.
But if even a substantial fraction of these results hold up...