橙子Joyce
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橙子Joyce
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On August 21, Ethereum co-founder Vitalik Buterin published a new article, “Obfuscation (Part Three): Local Mixing,” introducing a cryptographic obfuscation technique being explored—“Local Mixing”—and suggesting it could become a new foundational tool for cryptography after elliptic curves, RSA, and lattice cryptography.
Vitalik publishes “Local Mixing” cryptography research: exploring next-generation obfuscation techniques, or becoming a new type of cryptographic base primitive
Vitalik said that today’s mainstream obfuscation techniques mainly rely on complex mathematical assumptions, but they often come with extremely high computational overhead. Local mixing uses an entirely different approach: it does not rely on elliptic curves, large-integer factorization, or lattice cryptography. Instead, it draws on experience from symmetric cryptography and hash function design—by continuously scrambling, restructuring, and hiding circuit structures, it eliminates information leakage while keeping functionality unchanged. The main steps in local mixing include reversibility, hardening, mixing, splitting, crossing walk, and “gadgetization.” By adding random structures to circuits, rearranging logic gates, and introducing nonlinear hiding mechanisms, it becomes difficult for an attacker to recover the original computation logic.
Vitalik noted that the technique is still in an early stage; its security has not yet been validated through long-term testing and it faces challenges such as random attacks and linear analysis. However, he believes that local mixing represents a completely new direction for cryptographic exploration, with the goal of building more efficient indistinguishability obfuscation (iO) schemes. If local mixing breakthroughs are achieved, it could lead to new post-quantum public-key encryption solutions and accelerate the development of general-purpose obfuscation technologies. At present, the field still requires years of cryptanalysis and optimization validation, but AI-assisted research may significantly speed up the maturation process.
Vitalik also said that obfuscation techniques are viewed as the “last frontier” of cryptography because, in theory, other cryptographic primitives can be constructed based on obfuscation and one-way functions. Local mixing could not only reduce the cost of traditional obfuscation schemes, but also become an important direction for future cryptographic infrastructure.
Vitalik publishes “Local Mixing” cryptography research: exploring next-generation obfuscation techniques, or becoming a new type of cryptographic base primitive
Vitalik said that today’s mainstream obfuscation techniques mainly rely on complex mathematical assumptions, but they often come with extremely high computational overhead. Local mixing uses an entirely different approach: it does not rely on elliptic curves, large-integer factorization, or lattice cryptography. Instead, it draws on experience from symmetric cryptography and hash function design—by continuously scrambling, restructuring, and hiding circuit structures, it eliminates information leakage while keeping functionality unchanged. The main steps in local mixing include reversibility, hardening, mixing, splitting, crossing walk, and “gadgetization.” By adding random structures to circuits, rearranging logic gates, and introducing nonlinear hiding mechanisms, it becomes difficult for an attacker to recover the original computation logic.
Vitalik noted that the technique is still in an early stage; its security has not yet been validated through long-term testing and it faces challenges such as random attacks and linear analysis. However, he believes that local mixing represents a completely new direction for cryptographic exploration, with the goal of building more efficient indistinguishability obfuscation (iO) schemes. If local mixing breakthroughs are achieved, it could lead to new post-quantum public-key encryption solutions and accelerate the development of general-purpose obfuscation technologies. At present, the field still requires years of cryptanalysis and optimization validation, but AI-assisted research may significantly speed up the maturation process.
Vitalik also said that obfuscation techniques are viewed as the “last frontier” of cryptography because, in theory, other cryptographic primitives can be constructed based on obfuscation and one-way functions. Local mixing could not only reduce the cost of traditional obfuscation schemes, but also become an important direction for future cryptographic infrastructure.
@橙子Joyce 🧧🧧🧧🧧🧧🧧🧧🧧💰💸
橙子Joyce
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On August 21, Ethereum co-founder Vitalik Buterin published a new article, “Obfuscation (Part Three): Local Mixing,” introducing a cryptographic obfuscation technique being explored—“Local Mixing”—and suggesting it could become a new foundational tool for cryptography after elliptic curves, RSA, and lattice cryptography.
Vitalik publishes “Local Mixing” cryptography research: exploring next-generation obfuscation techniques, or becoming a new type of cryptographic base primitive
Vitalik said that today’s mainstream obfuscation techniques mainly rely on complex mathematical assumptions, but they often come with extremely high computational overhead. Local mixing uses an entirely different approach: it does not rely on elliptic curves, large-integer factorization, or lattice cryptography. Instead, it draws on experience from symmetric cryptography and hash function design—by continuously scrambling, restructuring, and hiding circuit structures, it eliminates information leakage while keeping functionality unchanged. The main steps in local mixing include reversibility, hardening, mixing, splitting, crossing walk, and “gadgetization.” By adding random structures to circuits, rearranging logic gates, and introducing nonlinear hiding mechanisms, it becomes difficult for an attacker to recover the original computation logic.
Vitalik noted that the technique is still in an early stage; its security has not yet been validated through long-term testing and it faces challenges such as random attacks and linear analysis. However, he believes that local mixing represents a completely new direction for cryptographic exploration, with the goal of building more efficient indistinguishability obfuscation (iO) schemes. If local mixing breakthroughs are achieved, it could lead to new post-quantum public-key encryption solutions and accelerate the development of general-purpose obfuscation technologies. At present, the field still requires years of cryptanalysis and optimization validation, but AI-assisted research may significantly speed up the maturation process.
Vitalik also said that obfuscation techniques are viewed as the “last frontier” of cryptography because, in theory, other cryptographic primitives can be constructed based on obfuscation and one-way functions. Local mixing could not only reduce the cost of traditional obfuscation schemes, but also become an important direction for future cryptographic infrastructure.
Vitalik publishes “Local Mixing” cryptography research: exploring next-generation obfuscation techniques, or becoming a new type of cryptographic base primitive
Vitalik said that today’s mainstream obfuscation techniques mainly rely on complex mathematical assumptions, but they often come with extremely high computational overhead. Local mixing uses an entirely different approach: it does not rely on elliptic curves, large-integer factorization, or lattice cryptography. Instead, it draws on experience from symmetric cryptography and hash function design—by continuously scrambling, restructuring, and hiding circuit structures, it eliminates information leakage while keeping functionality unchanged. The main steps in local mixing include reversibility, hardening, mixing, splitting, crossing walk, and “gadgetization.” By adding random structures to circuits, rearranging logic gates, and introducing nonlinear hiding mechanisms, it becomes difficult for an attacker to recover the original computation logic.
Vitalik noted that the technique is still in an early stage; its security has not yet been validated through long-term testing and it faces challenges such as random attacks and linear analysis. However, he believes that local mixing represents a completely new direction for cryptographic exploration, with the goal of building more efficient indistinguishability obfuscation (iO) schemes. If local mixing breakthroughs are achieved, it could lead to new post-quantum public-key encryption solutions and accelerate the development of general-purpose obfuscation technologies. At present, the field still requires years of cryptanalysis and optimization validation, but AI-assisted research may significantly speed up the maturation process.
Vitalik also said that obfuscation techniques are viewed as the “last frontier” of cryptography because, in theory, other cryptographic primitives can be constructed based on obfuscation and one-way functions. Local mixing could not only reduce the cost of traditional obfuscation schemes, but also become an important direction for future cryptographic infrastructure.
@橙子Joyce 🧧🧧🧧🧧🧧🧧🧧🧧💰💸
橙子Joyce
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On August 21, Ethereum co-founder Vitalik Buterin published a new article, “Obfuscation (Part Three): Local Mixing,” introducing a cryptographic obfuscation technique being explored—“Local Mixing”—and suggesting it could become a new foundational tool for cryptography after elliptic curves, RSA, and lattice cryptography.
Vitalik publishes “Local Mixing” cryptography research: exploring next-generation obfuscation techniques, or becoming a new type of cryptographic base primitive
Vitalik said that today’s mainstream obfuscation techniques mainly rely on complex mathematical assumptions, but they often come with extremely high computational overhead. Local mixing uses an entirely different approach: it does not rely on elliptic curves, large-integer factorization, or lattice cryptography. Instead, it draws on experience from symmetric cryptography and hash function design—by continuously scrambling, restructuring, and hiding circuit structures, it eliminates information leakage while keeping functionality unchanged. The main steps in local mixing include reversibility, hardening, mixing, splitting, crossing walk, and “gadgetization.” By adding random structures to circuits, rearranging logic gates, and introducing nonlinear hiding mechanisms, it becomes difficult for an attacker to recover the original computation logic.
Vitalik noted that the technique is still in an early stage; its security has not yet been validated through long-term testing and it faces challenges such as random attacks and linear analysis. However, he believes that local mixing represents a completely new direction for cryptographic exploration, with the goal of building more efficient indistinguishability obfuscation (iO) schemes. If local mixing breakthroughs are achieved, it could lead to new post-quantum public-key encryption solutions and accelerate the development of general-purpose obfuscation technologies. At present, the field still requires years of cryptanalysis and optimization validation, but AI-assisted research may significantly speed up the maturation process.
Vitalik also said that obfuscation techniques are viewed as the “last frontier” of cryptography because, in theory, other cryptographic primitives can be constructed based on obfuscation and one-way functions. Local mixing could not only reduce the cost of traditional obfuscation schemes, but also become an important direction for future cryptographic infrastructure.
Vitalik publishes “Local Mixing” cryptography research: exploring next-generation obfuscation techniques, or becoming a new type of cryptographic base primitive
Vitalik said that today’s mainstream obfuscation techniques mainly rely on complex mathematical assumptions, but they often come with extremely high computational overhead. Local mixing uses an entirely different approach: it does not rely on elliptic curves, large-integer factorization, or lattice cryptography. Instead, it draws on experience from symmetric cryptography and hash function design—by continuously scrambling, restructuring, and hiding circuit structures, it eliminates information leakage while keeping functionality unchanged. The main steps in local mixing include reversibility, hardening, mixing, splitting, crossing walk, and “gadgetization.” By adding random structures to circuits, rearranging logic gates, and introducing nonlinear hiding mechanisms, it becomes difficult for an attacker to recover the original computation logic.
Vitalik noted that the technique is still in an early stage; its security has not yet been validated through long-term testing and it faces challenges such as random attacks and linear analysis. However, he believes that local mixing represents a completely new direction for cryptographic exploration, with the goal of building more efficient indistinguishability obfuscation (iO) schemes. If local mixing breakthroughs are achieved, it could lead to new post-quantum public-key encryption solutions and accelerate the development of general-purpose obfuscation technologies. At present, the field still requires years of cryptanalysis and optimization validation, but AI-assisted research may significantly speed up the maturation process.
Vitalik also said that obfuscation techniques are viewed as the “last frontier” of cryptography because, in theory, other cryptographic primitives can be constructed based on obfuscation and one-way functions. Local mixing could not only reduce the cost of traditional obfuscation schemes, but also become an important direction for future cryptographic infrastructure.
@橙子Joyce 🧧🧧🧧🧧🧧🧧🧧🧧💰💸
橙子Joyce
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On August 21, Ethereum co-founder Vitalik Buterin published a new article, “Obfuscation (Part Three): Local Mixing,” introducing a cryptographic obfuscation technique being explored—“Local Mixing”—and suggesting it could become a new foundational tool for cryptography after elliptic curves, RSA, and lattice cryptography.
Vitalik publishes “Local Mixing” cryptography research: exploring next-generation obfuscation techniques, or becoming a new type of cryptographic base primitive
Vitalik said that today’s mainstream obfuscation techniques mainly rely on complex mathematical assumptions, but they often come with extremely high computational overhead. Local mixing uses an entirely different approach: it does not rely on elliptic curves, large-integer factorization, or lattice cryptography. Instead, it draws on experience from symmetric cryptography and hash function design—by continuously scrambling, restructuring, and hiding circuit structures, it eliminates information leakage while keeping functionality unchanged. The main steps in local mixing include reversibility, hardening, mixing, splitting, crossing walk, and “gadgetization.” By adding random structures to circuits, rearranging logic gates, and introducing nonlinear hiding mechanisms, it becomes difficult for an attacker to recover the original computation logic.
Vitalik noted that the technique is still in an early stage; its security has not yet been validated through long-term testing and it faces challenges such as random attacks and linear analysis. However, he believes that local mixing represents a completely new direction for cryptographic exploration, with the goal of building more efficient indistinguishability obfuscation (iO) schemes. If local mixing breakthroughs are achieved, it could lead to new post-quantum public-key encryption solutions and accelerate the development of general-purpose obfuscation technologies. At present, the field still requires years of cryptanalysis and optimization validation, but AI-assisted research may significantly speed up the maturation process.
Vitalik also said that obfuscation techniques are viewed as the “last frontier” of cryptography because, in theory, other cryptographic primitives can be constructed based on obfuscation and one-way functions. Local mixing could not only reduce the cost of traditional obfuscation schemes, but also become an important direction for future cryptographic infrastructure.
Vitalik publishes “Local Mixing” cryptography research: exploring next-generation obfuscation techniques, or becoming a new type of cryptographic base primitive
Vitalik said that today’s mainstream obfuscation techniques mainly rely on complex mathematical assumptions, but they often come with extremely high computational overhead. Local mixing uses an entirely different approach: it does not rely on elliptic curves, large-integer factorization, or lattice cryptography. Instead, it draws on experience from symmetric cryptography and hash function design—by continuously scrambling, restructuring, and hiding circuit structures, it eliminates information leakage while keeping functionality unchanged. The main steps in local mixing include reversibility, hardening, mixing, splitting, crossing walk, and “gadgetization.” By adding random structures to circuits, rearranging logic gates, and introducing nonlinear hiding mechanisms, it becomes difficult for an attacker to recover the original computation logic.
Vitalik noted that the technique is still in an early stage; its security has not yet been validated through long-term testing and it faces challenges such as random attacks and linear analysis. However, he believes that local mixing represents a completely new direction for cryptographic exploration, with the goal of building more efficient indistinguishability obfuscation (iO) schemes. If local mixing breakthroughs are achieved, it could lead to new post-quantum public-key encryption solutions and accelerate the development of general-purpose obfuscation technologies. At present, the field still requires years of cryptanalysis and optimization validation, but AI-assisted research may significantly speed up the maturation process.
Vitalik also said that obfuscation techniques are viewed as the “last frontier” of cryptography because, in theory, other cryptographic primitives can be constructed based on obfuscation and one-way functions. Local mixing could not only reduce the cost of traditional obfuscation schemes, but also become an important direction for future cryptographic infrastructure.
从0开始1688
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The biggest suspense after Apple’s leadership change in September: Will it really spend big to buy an AI giant?
Apple’s hardware chief John Ternus will take over as CEO this September from Tim Cook. Under the Tim Cook era, Apple was known for its scale and execution strength, but in the AI arms race it has seemed overly conservative. With the baton handoff in September, Wall Street is betting on whether the new boss can lead the world’s second-largest company through a truly meaningful strategic transformation.
Bank of America analyst Wamsi Mohan, in a recent research note, raised a key question: “Can Apple transition from an era driven by scale and execution to a new era driven by AI innovation?” This question has directly sparked market imagination about Apple’s future strategic direction.
Bank of America analyst Wamsi Mohan, in a recent research note, raised a key question: “Can Apple transition from an era driven by scale and execution to a new era driven by AI innovation?” This question has directly sparked market imagination about Apple’s future strategic direction.
@橙子Joyce 🧧🧧🧧🧧🧧🧧🧧🧧💰💸
橙子Joyce
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On August 21, Ethereum co-founder Vitalik Buterin published a new article, “Obfuscation (Part Three): Local Mixing,” introducing a cryptographic obfuscation technique being explored—“Local Mixing”—and suggesting it could become a new foundational tool for cryptography after elliptic curves, RSA, and lattice cryptography.
Vitalik publishes “Local Mixing” cryptography research: exploring next-generation obfuscation techniques, or becoming a new type of cryptographic base primitive
Vitalik said that today’s mainstream obfuscation techniques mainly rely on complex mathematical assumptions, but they often come with extremely high computational overhead. Local mixing uses an entirely different approach: it does not rely on elliptic curves, large-integer factorization, or lattice cryptography. Instead, it draws on experience from symmetric cryptography and hash function design—by continuously scrambling, restructuring, and hiding circuit structures, it eliminates information leakage while keeping functionality unchanged. The main steps in local mixing include reversibility, hardening, mixing, splitting, crossing walk, and “gadgetization.” By adding random structures to circuits, rearranging logic gates, and introducing nonlinear hiding mechanisms, it becomes difficult for an attacker to recover the original computation logic.
Vitalik noted that the technique is still in an early stage; its security has not yet been validated through long-term testing and it faces challenges such as random attacks and linear analysis. However, he believes that local mixing represents a completely new direction for cryptographic exploration, with the goal of building more efficient indistinguishability obfuscation (iO) schemes. If local mixing breakthroughs are achieved, it could lead to new post-quantum public-key encryption solutions and accelerate the development of general-purpose obfuscation technologies. At present, the field still requires years of cryptanalysis and optimization validation, but AI-assisted research may significantly speed up the maturation process.
Vitalik also said that obfuscation techniques are viewed as the “last frontier” of cryptography because, in theory, other cryptographic primitives can be constructed based on obfuscation and one-way functions. Local mixing could not only reduce the cost of traditional obfuscation schemes, but also become an important direction for future cryptographic infrastructure.
Vitalik publishes “Local Mixing” cryptography research: exploring next-generation obfuscation techniques, or becoming a new type of cryptographic base primitive
Vitalik said that today’s mainstream obfuscation techniques mainly rely on complex mathematical assumptions, but they often come with extremely high computational overhead. Local mixing uses an entirely different approach: it does not rely on elliptic curves, large-integer factorization, or lattice cryptography. Instead, it draws on experience from symmetric cryptography and hash function design—by continuously scrambling, restructuring, and hiding circuit structures, it eliminates information leakage while keeping functionality unchanged. The main steps in local mixing include reversibility, hardening, mixing, splitting, crossing walk, and “gadgetization.” By adding random structures to circuits, rearranging logic gates, and introducing nonlinear hiding mechanisms, it becomes difficult for an attacker to recover the original computation logic.
Vitalik noted that the technique is still in an early stage; its security has not yet been validated through long-term testing and it faces challenges such as random attacks and linear analysis. However, he believes that local mixing represents a completely new direction for cryptographic exploration, with the goal of building more efficient indistinguishability obfuscation (iO) schemes. If local mixing breakthroughs are achieved, it could lead to new post-quantum public-key encryption solutions and accelerate the development of general-purpose obfuscation technologies. At present, the field still requires years of cryptanalysis and optimization validation, but AI-assisted research may significantly speed up the maturation process.
Vitalik also said that obfuscation techniques are viewed as the “last frontier” of cryptography because, in theory, other cryptographic primitives can be constructed based on obfuscation and one-way functions. Local mixing could not only reduce the cost of traditional obfuscation schemes, but also become an important direction for future cryptographic infrastructure.
【Anthropic is expected to match or exceed SpaceX’s IPO record】
Previously, reports said that Anthropic’s preliminary revenue in the second quarter exceeded $11.5 billion, while it was only $787 million in the same period of 2025. By the end of July, the company’s annualized revenue run rate had reached $65 billion.
According to people familiar with the matter, the AI company Anthropic expects its IPO size to match or exceed the record set by SpaceX. As the AI company accelerates its preparations for going public, a mega-IPO is being lined up. The people familiar with the matter said that Anthropic is conducting related calculations and preparing to file for a potentially large IPO as early as later this month. They added that a recent investor communications meeting chaired by Chief Financial Officer Klao avoided discussing valuation. Data shows that at the time of its IPO, SpaceX—an aerospace company for rockets and satellites—raised $75 billion, becoming the largest initial public offering in history. Because it exercised so-called over-allotment options, the figure ultimately rose to $86.2 billion. This mechanism is typically triggered in the early period after the stock begins trading. Anthropic’s target reflects how leading companies in the AI industry are reshaping the tech investment landscape in an extremely short time. Previously, reports said that Anthropic’s preliminary revenue in the second quarter exceeded $11.5 billion, while it was only $787 million in the same period of 2025. By the end of July, the company’s annualized revenue run rate had reached $65 billion.
Previously, reports said that Anthropic’s preliminary revenue in the second quarter exceeded $11.5 billion, while it was only $787 million in the same period of 2025. By the end of July, the company’s annualized revenue run rate had reached $65 billion.
According to people familiar with the matter, the AI company Anthropic expects its IPO size to match or exceed the record set by SpaceX. As the AI company accelerates its preparations for going public, a mega-IPO is being lined up. The people familiar with the matter said that Anthropic is conducting related calculations and preparing to file for a potentially large IPO as early as later this month. They added that a recent investor communications meeting chaired by Chief Financial Officer Klao avoided discussing valuation. Data shows that at the time of its IPO, SpaceX—an aerospace company for rockets and satellites—raised $75 billion, becoming the largest initial public offering in history. Because it exercised so-called over-allotment options, the figure ultimately rose to $86.2 billion. This mechanism is typically triggered in the early period after the stock begins trading. Anthropic’s target reflects how leading companies in the AI industry are reshaping the tech investment landscape in an extremely short time. Previously, reports said that Anthropic’s preliminary revenue in the second quarter exceeded $11.5 billion, while it was only $787 million in the same period of 2025. By the end of July, the company’s annualized revenue run rate had reached $65 billion.
[Micron Launches Micron Research Laboratory; to Invest $10 Billion Over the Next Decade] Micron Technology announced the establishment of the Micron Research Laboratory, planning to invest $10 billion over the next ten years. The center will bring together customers, academia, government, and the broader semiconductor ecosystem to explore breakthrough results beyond current technology roadmaps, building on Micron’s technology and manufacturing leadership. Key research areas include critical memory technologies, advanced memory and computing architectures, packaging, and future semiconductor manufacturing. As the first research center of its kind in the United States dedicated to memory research, the Micron Research Laboratory will be anchored by the Boise flagship campus, supporting advanced research across cross-critical technology domains. The investment plan will also fund extensive university collaborations, global satellite laboratories, and deep ecosystem partnerships, building an interconnected research network focused on next-generation technologies for the AI era.
Partly True
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Verified
The U.S. Treasury steps in to support the market, pushing down the U.S. Treasury yields that have been pressuring global stock markets. The U.S. Treasury announced that it will at least double the size of its buyback program for long-term Treasury bonds. After the news broke, the prices of ultra-long Treasury bonds issued by the U.S. government surged sharply. The backdrop to this move is that global long-term bond markets have recently suffered large-scale selling, and the yield on the 30-year U.S. Treasury briefly spiked to the highest level since 2007 on Monday. At the same time, traders are preparing for a new issuance auction of $16 billion worth of 20-year Treasury notes scheduled to take place soon. In a statement, the U.S. Treasury said, “By increasing the size of the repurchase operations, the Treasury aims to provide stronger liquidity support for the long-dated nominal Treasury market. Within these maturity ranges, market participants have consistently demonstrated strong and stable appetite, which is evidenced by the large volume of high-quality bids the Treasury regularly receives in its long-dated Treasury repurchase operations.” Under the accelerated repurchase plan, the Treasury will focus on repurchasing Treasuries in the 10-to-20-year and 20-to-30-year maturity ranges. Since the end of June, the U.S. Treasury markets in these maturities have been plagued by a “buyer walkout,” with investors’ willingness to take on the bonds clearly lacking. According to the Treasury’s announcement, the government will increase the maximum size of each repurchase operation “by at least” double—from $2 billion to “at least” $4 billion.
#黄金
#silver
#黄金
#silver
A single greeting, carries the tenderness of Qixi; a blessing, is the softness of Qixi. May all the deep feelings in this world not be let down, may all true love be cherished well, and may every rush of pursuit be met with the gentlest echoes. 🐦🔥🐲🌹🌹🌹🌹🌹🌹🌹🌹🌹
JPMorgan Conducts On-Site Research on Tesla: Two Core Narratives—Robotaxi and Optimus—Their Commercialization Path Is Gradually Becoming Clear.
The expansion of Tesla’s Robotaxi fleet will see a clear acceleration from late 2026 to early 2027, with the key trigger already identified: the in-year release of FSD v15. For Optimus, the Gen 3 design has been finalized, the supply chain is largely locked in, and after the start of mass production (SoP), the initial deployment target is to enter the “Optimus Academy” training phase in the second half of 2026, with external commercial sales achieved as early as the second half of 2027.
Tesla’s two core narratives—scaling up Robotaxi deployments and commercializing Optimus humanoid robots—are moving from concept to an execution path that can be quantified. JPMorgan recently carried out an on-site research visit at Tesla’s Fremont factory and held meetings with the company’s investor relations team. Overall, the analysts gave positive assessments of the advancement pace for the two business lines, believing that both are broadly aligned with the timeline previously disclosed by management.
According to a JPMorgan report, the key trigger for expanding the Robotaxi fleet has been clearly pinned to the in-year launch of FSD v15. Management said that technical validation work for a small-scale Cybercab test fleet is continuing, and about 40% of the core v15 technical modules have already been tested in the Robotaxi fleet, with initial feedback described as positive;
At the same time, the company intends to control the number of Model Y units converted to the Robotaxi fleet, indicating confidence in the near-term ability to deliver Cybercab at scale.
For Optimus, the Gen 3 design has been finalized, the supply chain is largely locked in, and production lines are being installed at the Fremont factory. After mass production starts (SoP), the initial deployment target is to enter the “Optimus Academy” training phase in the second half of 2026, with external commercial sales as early as the second half of 2027.
JPMorgan maintains a Neutral rating on Tesla with a target price of $445. At the time the report was published, the stock price was $339.30. The analysts’ view is that the expansion of the Robotaxi fleet will accelerate noticeably from late 2026 to early 2027; the Optimus commercialization path is clear, and an improving FSD penetration rate, together with a lineup of new vehicle models, will support a near-term rebound in demand.
Robotaxi scaling up: FSD v15 is the key switch
Optimus: Production line installation underway; commercialization path in three stages
FSD: From configuration options to the core driver of purchasing
Demand recovery coexists with pressure on gross margins
The expansion of Tesla’s Robotaxi fleet will see a clear acceleration from late 2026 to early 2027, with the key trigger already identified: the in-year release of FSD v15. For Optimus, the Gen 3 design has been finalized, the supply chain is largely locked in, and after the start of mass production (SoP), the initial deployment target is to enter the “Optimus Academy” training phase in the second half of 2026, with external commercial sales achieved as early as the second half of 2027.
Tesla’s two core narratives—scaling up Robotaxi deployments and commercializing Optimus humanoid robots—are moving from concept to an execution path that can be quantified. JPMorgan recently carried out an on-site research visit at Tesla’s Fremont factory and held meetings with the company’s investor relations team. Overall, the analysts gave positive assessments of the advancement pace for the two business lines, believing that both are broadly aligned with the timeline previously disclosed by management.
According to a JPMorgan report, the key trigger for expanding the Robotaxi fleet has been clearly pinned to the in-year launch of FSD v15. Management said that technical validation work for a small-scale Cybercab test fleet is continuing, and about 40% of the core v15 technical modules have already been tested in the Robotaxi fleet, with initial feedback described as positive;
At the same time, the company intends to control the number of Model Y units converted to the Robotaxi fleet, indicating confidence in the near-term ability to deliver Cybercab at scale.
For Optimus, the Gen 3 design has been finalized, the supply chain is largely locked in, and production lines are being installed at the Fremont factory. After mass production starts (SoP), the initial deployment target is to enter the “Optimus Academy” training phase in the second half of 2026, with external commercial sales as early as the second half of 2027.
JPMorgan maintains a Neutral rating on Tesla with a target price of $445. At the time the report was published, the stock price was $339.30. The analysts’ view is that the expansion of the Robotaxi fleet will accelerate noticeably from late 2026 to early 2027; the Optimus commercialization path is clear, and an improving FSD penetration rate, together with a lineup of new vehicle models, will support a near-term rebound in demand.
Robotaxi scaling up: FSD v15 is the key switch
Optimus: Production line installation underway; commercialization path in three stages
FSD: From configuration options to the core driver of purchasing
Demand recovery coexists with pressure on gross margins
Verified
AI companies reach out for help: OpenAI records computer actions, while Google uses uploaded content to train AI.
Axios begins investigating what user data AI companies are actually collecting.
The findings show that chat logs aren’t enough anymore. Now they also want to know what you click on your computer, what photos you upload, and what content you’ve viewed—then use that data for memory, personalization, and advertising.
OpenAI has added Computer History. Once Mac users manually enable it, ChatGPT and Codex can record your clicks, inputs, and switches within specific apps and websites, gradually building a long-term work memory about you. The feature is turned off by default; it doesn’t record your screen or audio. OpenAI says temporary action logs won’t be used to train its models.
Google is even more aggressive. A new Search Services History will save images, documents, and audio/video that users upload through services like Lens, Search Live, and Translate—and it can also be used to train generative AI. For accounts that meet the criteria, it’s enabled by default; if you want to opt out, you have to do it yourself. Even some data that is later unlinked from an account may be retained for up to 4 years after entering the training process.
Advertising has kept up too. Meta will use users’ interactions with Meta AI to adjust the content and ads on Facebook and Instagram; OpenAI and Google are also exploring ad models for chatbots. The better AI understands you, the more detailed the “portrait” the ad system has in its hands.
What used to be a concern was that chat logs would be used for training. Now, even how you work on your computer—and what you throw into Google—has started to become data in the hands of AI companies.
Axios begins investigating what user data AI companies are actually collecting.
The findings show that chat logs aren’t enough anymore. Now they also want to know what you click on your computer, what photos you upload, and what content you’ve viewed—then use that data for memory, personalization, and advertising.
OpenAI has added Computer History. Once Mac users manually enable it, ChatGPT and Codex can record your clicks, inputs, and switches within specific apps and websites, gradually building a long-term work memory about you. The feature is turned off by default; it doesn’t record your screen or audio. OpenAI says temporary action logs won’t be used to train its models.
Google is even more aggressive. A new Search Services History will save images, documents, and audio/video that users upload through services like Lens, Search Live, and Translate—and it can also be used to train generative AI. For accounts that meet the criteria, it’s enabled by default; if you want to opt out, you have to do it yourself. Even some data that is later unlinked from an account may be retained for up to 4 years after entering the training process.
Advertising has kept up too. Meta will use users’ interactions with Meta AI to adjust the content and ads on Facebook and Instagram; OpenAI and Google are also exploring ad models for chatbots. The better AI understands you, the more detailed the “portrait” the ad system has in its hands.
What used to be a concern was that chat logs would be used for training. Now, even how you work on your computer—and what you throw into Google—has started to become data in the hands of AI companies.
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