Google pulls ahead with pre‑training; OpenAI's comeback plan named ‘Shallotpeat’
Google’s newest AI benchmarks are pulling the focus away from flashy demos and onto how models are actually built. Meanwhile, OpenAI is rolling out a comeback plan they’ve nicknamed “Shallotpeat,” and even its leaders seem to admit there’s a gap. In a recent note, Sam Altman gave Google a nod, saying the company’s emphasis on pre-training stands out.
That comment lands just as the field is still arguing whether the huge data-feeding stage that powers large language models matters any more, or if fine-tuning tricks have taken over. The point, I think, is that pre-training sets how wide a model’s language grasp is before any task-specific tweaks. If a rival can soak up the world’s text faster, they get a head start that later polishing can only boost.
Altman’s concession hints that OpenAI might be rethinking its strategy. As he puts it, the next line explains why you can’t just skip the foundational phase.
Pre-training isn't dead, it's crucial What's interesting is the role that pre-training played in Google's success. In his note, Altman admitted that Google has "been doing excellent work recently," especially in pre-training. This fundamental phase, where an AI model learns from vast amounts of data, seemed to have hit its limits.
But Google's success shows that while massive performance leaps may not be on the immediate horizon, effective advantages can still be gained. This is a particularly sore spot for OpenAI, as the company has reportedly struggled to make progress in pre-training. This prompted OpenAI to focus more on "reasoning" models.
Google’s still ahead. An internal OpenAI memo paints a stark picture, warning that recent gains in pre-training could give Google a short-term edge. Altman’s note concedes that Google’s work in the fundamental pre-training phase, where models swallow massive data, has been impressive, and he stresses that pre-training “isn’t dead, it’s crucial.” Still, the memo hints at uncertainty: the vibe is “rough for a bit,” and the path forward isn’t fully mapped.
What will “Shallotpeat” actually bring? The codename sounds like a focused push to blunt Google’s momentum, but details are thin. If OpenAI can match or outscale Google’s pre-training effort, the balance could tip; if not, the gap may simply widen.
Both companies seem locked in a race where foundational model training matters more than ever. Whether OpenAI’s response will close the lead remains unclear, and the wider market impact is still up in the air. Stakeholders are watching the internal dynamics, but no public roadmap has surfaced. The memo’s tone feels more cautious than confident, underscoring the pressure.
Related Reading
Browse all OpenAI news →
Business & Startups Oracle, NVIDIA deepen tie-up to speed sovereign AI and government digital shift
Business & Startups Skilling programs lag AI; students must prioritize aspiration and depth
Business & Startups EPAM and Cursor partner to scale AI coding for global enterprise customers
Related Topic OpenAI launches ChatGPT shopping agent that uses memory data to compare products
LLMs & Generative AI
Related Topic OpenAI says AI saves knowledge workers 40‑80 minutes; use yields five‑fold gains
LLMs & Generative AI
Common Questions Answered
What is the name of OpenAI's comeback plan mentioned in the article?
OpenAI's comeback plan is codenamed “Shallotpeat.” The memo references this initiative as the company's strategy to regain competitive footing after acknowledging Google's recent advances.
Why did Sam Altman praise Google's recent work, according to the article?
Sam Altman highlighted Google's focus on pre‑training as a key differentiator, stating that the company has been doing excellent work in that fundamental phase. He emphasized that pre‑training isn’t dead and remains crucial for model performance.
How does the article describe the impact of Google's pre‑training success on OpenAI?
The article notes that Google's success in pre‑training could create temporary economic headwinds for OpenAI, potentially affecting its market position. OpenAI's internal memo warns that these advances may pose short‑term challenges for the rival.
What shift in industry conversation does the article attribute to Google's latest AI benchmarks?
Google’s latest benchmarks have moved the discussion from headline‑grabbing demos to the mechanics of model development, especially the pre‑training stage. This shift underscores the growing importance of data‑injection and foundational training phases.