Anthropic launches Claude Sheets, an AI spreadsheet competitor

Anthropic announced on Monday (9) the launch of two new iterations of its artificial intelligence models: Claude Fable 5.2 and Claude Mythos 5.2. These tools incorporate notable improvements in areas such as reasoning, programming, and visual interpretation, although their launch occurs during an intense debate about AI's ability to drive its own development.

According to the company, the newly released models demonstrate greater clarity in communication and offer more agile responses. Specifically, Fable 5.2 saw its entry fee decrease from US$ 10 to US$ 8 per million tokens, representing a 20% reduction (equivalent to about R$ 43). Furthermore, Anthropic reports that this model's responses became 30% faster across various complexity levels.

Access to Mythos 5.2 will be limited to organizations validated by the company itself, including those involved in cybersecurity focused programs. On the other hand, Fable 5.2 is already accessible through the Anthropic API and cloud computing platforms.

This launch follows a report issued by the AI safety organization, METR, just a few days prior. This study indicated that Anthropic's developed models are progressing almost twice as fast as before, an advancement attributed partly to the use of AI in the development cycle itself.

The analysis, conducted over eleven weeks and published on November 5, calculated that the performance of the company's models in well-defined tasks advanced 1.9 times faster since October 2025 compared to the preceding period. This finding reignited conversations about the concept of recursive self-improvement (RSI), which describes the potential for AI systems to assist in improving future versions of themselves, thereby accelerating consecutive technological generations.

However, METR made important caveats to its study, classifying the estimate as highly uncertain; the actual acceleration rate could vary between 1.5 and 2.5 times the historical pace. The study also highlighted that AI does not yet have the capacity to generate highly relevant contributions fully autonomously in the crucial phases of model training.

Additionally, Anthropic informed that Fable 5.2 was used in scientific research before its public release. Results credited to this model include solving two pending problems in theoretical physics and formalizing a proof for Fermat's Last Theorem. The company also mentioned that its models helped engineers finalize software migrations considered impractical, conceive three functional electronic devices from scratch, and advance in robotics-related evaluations.

In another disclosure made on Monday, the startup Physical Superintelligence presented a new demonstration regarding the Aaronson-Ambainis conjecture, a topic relevant to defining the theoretical limits of quantum computation. This company claimed to have achieved this result using an undisclosed Anthropic model, although the developer did not confirm whether the specific tool was Fable 5.2.

Artificial intelligence (AI) may be driving its own progress. An independent examination conducted by the non-profit organization Model Evaluation and Threat Research (METR) indicated that models developed by Anthropic are progressing almost twice as fast as before. This is partly due to the company's own use of AI systems to create more powerful versions of its technology.

The study, published this Thursday (5th), calculates that the advancement in the capabilities of Anthropic's models in specific tasks increased at a rate of 1.9 times since October 2025, compared to the previous pace.

According to METR, approximately 80% of this current acceleration is linked to the application of AI in the company's research and development activities. However, the estimate has a high degree of uncertainty.

The evaluation was carried out over an 11-week period, covering August to October 2026. Researchers had access to Anthropic's internal data, interviewed employees, and analyzed information on the performance of models that have not yet been made public.

The organization also found that the increase in computational capacity used for training does not justify the observed acceleration. The study establishes a crucial distinction: most of the progress still derives from the assistance provided by AI to experts, not from the autonomous execution of the entire development cycle.

METR stated that it found no evidence that current systems can offer highly relevant and fully independent contributions in the most critical phases of model training. Despite this, researchers detected signs that such participation may become more prominent in the future.

The advance noted by METR deserves attention because it is connected to the concept of recursive self-improvement, known by the acronym RSI. This idea posits that AI systems can increasingly contribute to the generation of new model versions. By assisting in the development of their successors with more competent systems, the process tends to gradually accelerate.

Although this scenario has not yet been achieved in a completely autonomous manner, it raises important questions about the speed of technological evolution. One concern highlighted by METR is the potential for this acceleration to become cumulative, where more advanced models assist in developing even more capable systems, which in turn would intensify the process.

The organization also did not identify clear impediments related to computing power, data availability, or experiments that would certainly block new advances in the next twelve months. However, the researchers emphasized that this analysis is also subject to uncertainties.

Despite the findings, METR recognizes significant limitations. The 1.9-fold acceleration was calculated based on performance indicators in well-defined tasks, which can be assessed through automated tests or language models. This does not imply that all aspects of AI are evolving at the same pace.

Additionally, Anthropic had the prerogative to remove confidential information from the report. According to METR, much of the evidence considered most pertinent to its conclusions was omitted, which complicates an independent assessment of all details.

The organization also highlights the uncertainty about what portion of the acceleration can be directly attributed to the use of AI, especially regarding the progress recorded at the end of 2025.

The results emerge at a time when Dario Amodei, CEO of Anthropic, advocates for prudence in the development of increasingly sophisticated systems. In September, the executive called on the sector to slow down the pace of technological capability advancement so that safeguards could keep up with the pace of improvements.

The study itself points out that understanding the speed of this evolution is vital for risk assessment. If systems begin to collaborate in a progressively more significant way in the development of their replacements, monitoring and control work may also become more complex.

Anthropic disclosed in an update to its S-1/A prospectus, submitted to the U.S. Securities and Exchange Commission (SEC), that it may be close to creating an artificial intelligence capable of accelerating its own enhancement.

Although the company states it has not yet reached this phase, its projections suggest this could happen in the near future. This technology, known as Recursive Self-Improvement (RSI), describes a point where AI systems can improve their own development processes, boosting the evolution of their capabilities.

This perspective generates divergence: critics warn that such advances could result in extremely powerful, human-out-of-control systems capable of causing harm while pursuing their objectives. On the other hand, enthusiasts see RSI as a chance to increase productivity and speed up scientific discoveries.

Anthropic acknowledges both views. In the document sent to the SEC, the company mentions that it already uses AI in its R&D activities but warns that this approach carries a significant safety risk, especially if the pace of progress is drastically accelerated.

The prospectus update introduces new warnings in the risk factors section. Anthropic revealed that it has already used AI systems to create new models without realizing at the time the magnitude of the capacity gains achieved. The increased use of AI in research may also cause models to evolve faster than the company's ability to implement safety, alignment, and protection measures.

According to the document, internal estimates and forecasts for future models indicate that the company may soon reach what its Responsible Scaling Policy calls 'dramatically accelerated AI-attributable progress.' However, the company emphasizes that none of its current models have been classified as having exceeded this limit, and data evaluation is ongoing.

Despite this possibility, Anthropic declares that it does not foresee using Claude to autonomously design and build successive generations of advanced models without relevant human supervision or understanding. The company also plans to revise its Responsible Scaling Policy to ensure humans maintain control over the development of its most sophisticated models.

It is important to note that the filings with the SEC fulfill disclosure obligations but also serve as a means for the company to present its expectations to the market. Anthropic stresses that Claude's capabilities have improved this year, notably in programming, mathematics, and cybersecurity, although no current model has been considered by the company to have reached the stage of recursive self-improvement.