ANTHROPICAnthropic tokenized stock (PreStocks) Price

Anthropic co-founder Jack Clark has revised his prediction for when AI will achieve Recursive Self-Improvement (RSI) from 2028 to 2027, a shift Elon Musk endorsed. This signals a potential near-term threshold where AI, having demonstrated core creativity in mathematics and research, could begin designing and improving itself autonomously. Key developments include AI solving complex mathematical problems with novel proofs and showing improved "scientific taste" in research intuition, moving beyond mere pattern recognition. The article warns that RSI could trigger an intelligence explosion, rapidly accelerating progress beyond human control or comprehension. This would extend AI's impact from digital to physical realms: supercharging scientific discovery (e.g., new materials, drugs), advancing robotics (like Tesla's Optimus and NVIDIA's GR00T), and disrupting economic and labor structures by automating cognitive and creative work. A 2025 report titled "AI 2027" outlined a plausible path where AI agents integrate into workflows by 2025, automate programming by 2027, and potentially trigger a post-2027 intelligence explosion. This timeline represents a critical countdown, highlighting that AI's capability growth may outpace society's ability to adapt or establish control mechanisms. While 2027 is not a guaranteed deadline, it underscores a pivotal and potentially dangerous transition point for human civilization as it approaches the dawn of a new era shaped by artificial superintelligence (ASI).

Anthropic faces valuation pressure for its potential IPO as its revenue growth slows. In Q3, revenue reached $16.8 billion, a 45% sequential increase, which was a significant drop from the over 140% growth seen in Q2. This slowdown has led some potential investors to suggest lowering the IPO valuation expectations, with discussions now around figures possibly under $1.5 trillion, down from earlier informal bank estimates of approximately $2 trillion. The deceleration reflects increased competitive pressures from OpenAI, Google, Meta, and open-source models. While Anthropic has achieved adjusted profitability for two consecutive quarters and positive cash flow in Q3, concerns are growing. Investors are scrutinizing whether future growth can justify high valuations, especially given Wall Street's expectations for a high annualized revenue run rate. Furthermore, Anthropic's massive planned infrastructure investment—reportedly over $500 billion in chips and infrastructure over the next decade—adds to the focus on whether revenue growth can translate into sustainable cash flow and profit. In a climate of rising financing costs and broader pressure on AI-related assets, the market is applying stricter scrutiny to the balance between growth, investment returns, and capital expenditure for AI companies.

Breaking news: Anthropic co-founder Jack Clark has significantly revised his timeline for AI achieving Recursive Self-Improvement (RSI), moving the prediction from 2028 to 2027. This announcement, echoed by Elon Musk, has sent shockwaves through the tech community. The core shift is driven by AI's recent breakthrough in demonstrating what was once considered uniquely human: true scientific creativity and "good research taste." AI systems are now solving advanced mathematical problems and generating novel proofs, indicating a leap in logical reasoning and innovative capacity. This erosion of the "creativity barrier" suggests AI is nearing the ability to recursively improve its own architecture. The implications are profound. Post-RSI, AI could rapidly advance scientific discovery (e.g., new materials, drugs) and accelerate robotics development, as seen with systems like NVIDIA's GR00T. An AI-driven "intelligence explosion" could reshape labor markets and economic structures, concentrating immense power. A pivotal 2026 report, "AI 2027," outlines a potential scenario where AI achieves full coding automation by early 2027, triggering an uncontrollable feedback loop of self-improvement by late 2027. While not a certainty, this timeline highlights a critical window: AI's capability growth may soon outpace humanity's ability to adapt or implement control mechanisms. The year 2027 marks a potential historic threshold—the dawn of a new era where humanity transitions from creator to observer of superintelligent systems.

Anthropic's credit rating has been revealed for the first time. According to documents obtained by the Financial Times, KBRA assigned Anthropic a BB+ issuer rating in June—the highest speculative-grade (junk) score, just one notch below investment grade. The rating was issued before Anthropic completed a $35 billion chip financing deal led by Apollo and had never been publicly disclosed. The rating directly affects Anthropic's financing prospects. Wall Street banks are preparing a $60 billion new debt package to help Anthropic acquire more custom AI chips developed jointly by Google and Broadcom, including $18 billion in subordinated debt. Whether Anthropic can cross the investment-grade threshold will determine whether it can access a broader group of institutional investors such as life insurers and pension funds at lower cost. The BB+ rating, with a stable outlook, applies to about $4.4 billion of subordinated debt within the $35 billion financing package—the portion directly exposing investors to Anthropic's credit risk; the rest is guaranteed by chipmaker Broadcom. The subordinated debt was issued at a yield of about 8.5%, while senior debt carried a rate of 5.75%. The rating was made with limited disclosure. KBRA received financial information including revenue, adjusted operating income, Q1 2026 annualized operating revenue, and internal Q2 forecasts, but key metrics such as free cash flow and EBITDA were not disclosed. Analysts relied on assumptions and ultimately used a "risk scoring" approach instead of a full financial model. At its pre-IPO investor presentation on Wednesday, Anthropic disclosed Q3 revenue grew nearly 50% quarter-over-quarter to $16.8 billion, with two consecutive quarters of adjusted profitability. However, growth has slowed from early in the year, and the latest figures fell short of some of the most optimistic expectations. Anthropic had forecast Q2 revenue of $10.9 billion, but actual figures exceeded expectations at $11.5 billion. As of end-June, the five-year-old company had zero debt on its own balance sheet, having relied on partners with better credit and special purpose vehicles for financing. Anthropic may also issue up to $42 billion in convertible notes to pay Broadcom for semiconductor leases, but KBRA was not given detailed terms. KBRA is smaller than Moody's, S&P, and Fitch, which will ultimately determine Anthropic's official credit rating after listing. Bank advisors to Anthropic and rival OpenAI have lobbied these major agencies for investment-grade ratings post-IPO. Investors expect OpenAI's IPO valuation to exceed $2 trillion. Obtaining an investment-grade rating is crucial to Anthropic's long-term financing strategy. The company expects to invest over $500 billion in computing resources and infrastructure over the next decade—a massive capital expenditure plan seen as a key pillar supporting the U.S. stock market investment boom.

Anthropic's Mythos 5 has achieved a breakthrough in quantum computing by autonomously designing quantum circuits that outperform human-optimized designs. Given only plain-language descriptions of eight foundational quantum circuits in chemistry, optimization, physics simulation, and number theory, the AI ran a fully automated closed loop: it wrote circuit designs in Python, received scores based on qubit count and gate count, and iteratively refined its work without human intervention. Within 53 hours, it beat the best publicly available human designs on all eight tasks. Two results stand out. First, in modular inversion for elliptic curve cryptography, existing divsteps algorithms were considered impractical on quantum computers because they generate branch history that cannot be discarded due to reversibility requirements. Mythos 5 derived entirely new algebraic identities to reconstruct that history from the result, producing the first reversible quantum divsteps implementation that needs no branch storage—cutting gate count by 17x with only 12% more qubits. Second, it redesigned the Reed-Solomon decoder inside Google's Decoding Quantum Interferometry algorithm, replacing the extended Euclidean approach with Berlekamp-Massey, which matches quantum circuit constraints. It then used a self-written simulator running 403 million samples to measure exception rates and reduced memory from 665 qubits to 19, achieving a 12x reduction in gate count. The work suggests software can compensate for immature quantum hardware, potentially accelerating useful quantum computing by years.