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  1. TMTPost · AGIOpinion
    AI score51

    "You've Been Replaced by AI": Short Drama Creators in 2026

    Xiaguang She interviewed multiple overseas short drama practitioners, documenting that in 2026 live-action short drama shooting projects decreased by 30% to 50% year-on-year, and actor audition calls dropped from twenty to thirty per week to single digits. The article mentions that the shooting cost of one overseas live-action short drama is about 150,000 USD, while the cost of an AI short drama may be only one-tenth of that, and it outlines the competitive landscape of three forces: Chinese teams, overseas transformation teams, and AI-native entrepreneurs. The article also states that TikTok's short drama revenue-sharing coefficient was lowered, with the share per ten thousand views falling from about 30 USD to a few USD.

    #English text is being prepared.#Video#Industry news

  2. TMTPost · AGIOpinion
    AI score73

    Meta Q3 earnings: advertising props up 97% of revenue, Muse still burning money

    Meta Q3 revenue was $64.6 billion, up 26% year-over-year, of which advertising contributed $63.06 billion, accounting for 97.6% of total revenue. The personal agent Muse, launched on September 8, surpassed 10 million downloads within 40 days of launch, but high capital expenditure turned free cash flow negative at $2.12 billion, and the full-year Capex guidance floor was raised from $130 billion to $135 billion. Muse currently mainly relies on subscription fees, with shopping being the most frequent use case; more than 25% of users have used the shopping feature, with average spend per transaction exceeding $200.

    #Industry news#Agents#OpenAI

  3. TMTPost · AGIOpinion
    AI score78

    Pichai Reviews Gemini 4 Argon: Why 3.5 Pro Was Cut

    Google CEO Pichai revealed in the "Sources" interview that Gemini 4 Argon processed about 25 trillion tokens in 72 hours of launch, 3 times that of Gemini 3.0 in the same period, and is still rate-limited due to compute constraints. He explained for the first time the reason for cutting Gemini 3.5 Pro: the team found a gap in the model on Agentic Coding, first used the Flash version to complete intensive iterations from 3.5 to 3.8 in about 3 months, while Argon pretraining had already been completed at that time, so they injected the accumulated gains into Argon post-training. He also mentioned that Google internally has entered the RSI stage of researchers and models collaborating, and said the next-generation Gemini 5.0 will be much stronger than Argon.

    #Industry news#Google#DeepMind

  4. TMTPost · AGIOpinion
    AI score70

    Terence Tao and Deng Yu in conversation: AI math results are "toxic waste," the problem lies in how they are released

    Terence Tao and this year's newly minted Fields Medalist Deng Yu discussed on the SAIR Foundation podcast the controversy sparked by OpenAI's mass release of AI math results; Tao called such bulk problem-solving output a kind of byproduct, or even "toxic waste." The two proposed that the boundaries between problem-solving and understanding are diverging, argued that AI results must come with explanations and traceable citations, that mathematicians should be involved at project inception, and introduced the Open Math OS project launched by SAIR, which first integrates existing open-source models and tools and hopes to build its own model in a few months.

    #Industry news#Papers/Research#Open-source ecosystem

  5. TMTPost · AGIOpinion
    AI score58

    San Francisco AI venture capital data packaging: buying GitHub stars for 6 cents, annualizing two-week orders into full-year ARR

    TMTPost AGI sorts through the data packaging tactics in the San Francisco AI venture capital circle, including multiplying a $3 million order from two weeks by 26 to claim externally about $80 million in ARR, startups mutually signing $5 million letters of intent, and buying GitHub stars at 6 cents each. The article also mentions that such practices likewise exist in the circles of large model labs and computing power centers, and cites industry insiders saying that the previous company that inflated $220 million in revenue by swapping invoices has already gone bankrupt.

    #English text is being prepared.#Industry news

  6. NumeramaOpinion
    AI score68

    Anthropic security lead warns the AI vulnerability-discovery crisis will last about another 18 months

    Jason Clinton, Anthropic's deputy head of information security, said on X that the security crisis brought by AI discovering software vulnerabilities in large numbers will continue to worsen for about 18 months before it may improve, and called on security leaders to secure resources from their boards as soon as possible. The article takes two severe PHP vulnerabilities named PHP2Shell as an example, saying that Wiz used Google's Gemini 4 Argon and OpenAI's GPT-5.6 Sol to discover this vulnerable code that has existed for more than a decade, while Calif researcher Ryan Austin discovered and reported it earlier on August 1 with the help of GPT-5.6 Sol, forming two independent discoveries. Clinton previously also predicted that open-weight models will reach equivalent cybersecurity capabilities within 7 to 10 months.

    #Safety / alignment#Agents#OpenAI

  7. Cailian PressOpinion
    AI score58

    Overseas AI Short Drama Going Global Survey: Volume-Run Window Narrows, Money Is Not So Easy to Earn

    Several AI short drama practitioners judge that the overseas low-cost volume-running stage may have only a few months left, and crude volume stacking is closing; relying only on premiumization cannot solve everything once and for all. DataEye data shows that from January to September 2026, overseas micro short drama APP dual-end in-app purchase revenue exceeded 2.1 billion USD and downloads exceeded 2.2 billion; the top three on the revenue list, DramaBox, ReelShort, and NetShort, together account for about 50% of the total revenue of the TOP20. Zhang Yi of iiMedia Research believes that the key to the next stage is not who makes more, but who can form a closed loop fastest.

    #English text is being prepared.#Video#Industry news

  8. WallstreetcnOpinion
    AI score56

    The Personal Agent battle spreads to hardware: the different paths of Qwen, Shokz, viaim and Bee

    Wallstreetcn reviewed the progress of Personal Agents entering AI glasses, earphones and recording devices: on October 13, Qwen released the AI glasses N1, N1 Pro and AI clip-on earphones, with the glasses priced from 2,218 yuan and the earphones at a first-sale price from 1,099 yuan, and stated that AI wearables are Qwen's extension into the physical world. The article compares different divisions of labor, such as Shokz OpenFit 2 AI calling on Qwen for transcription minutes, viaim using its own Agent to orchestrate other Agents, and Amazon's Bee integrating with Alexa+, and points out that selling hardware is only the first step; long-term revenue depends on context management and subscription services.

    #English text is being prepared.#Agents#English text is being prepared.

  9. WallstreetcnOpinion
    AI score51

    Inside Intel's Fabs: Chips Head Toward 3D Stacking by 2045, Mass Production of New Structures to Take About a Decade

    Dwarkesh Patel visited Intel's fabs and research labs for two days, discussing gate-all-around, backside power delivery, CFET and advanced packaging with five technical leaders, concluding that by 2045 chips will continue to develop toward 3D stacking, but each new structure will take about a decade to work through heat dissipation and integration challenges, and engineers have about four years of visibility into the technology roadmap. Intel CTO Pushkar Ranade estimates that existing global equipment is roughly only enough to double advanced-process wafer output, while AI compute has grown 3x per year for a decade; equipment orders take 18 months to receive, and new fabs will basically not come online until the end of this decade.

    Same story · 2 reports

    #Industry news#English text is being prepared.#English text is being prepared.

  10. WallstreetcnOpinion
    AI score55

    TS Lombard speculates the AI bubble may burst in early 2028, with U.S. tech stocks potentially plunging 40%

    In an October 22 research note, TS Lombard Chief Macro Strategist Dario Perkins projected that the AI capital expenditure boom could end in early 2028, with the S&P 500 falling 30%, tech stocks plunging 40%, and about $20 trillion in market value evaporating. The report argues that current AI revenue growth mainly comes from the capital expenditure cycle among tech giants and debt financing, and lists six chain-reaction triggers: revenue falling short of expectations, rising credit risk, depreciation pressure, an IPO wave, the semiconductor cycle, and regulatory and safety concerns. The report estimates that U.S. GDP would fall by about 2 percentage points and about 800,000 data center-related jobs would be lost, but private-sector balance sheets are healthy and the Federal Reserve has ample room to cut rates, making the recession closer to those of 1990 or 2001 than to 2008.

    #English text is being prepared.#Industry news#English text is being prepared.

  11. WallstreetcnOpinion
    AI score59

    Nomura: AI growth panic replaces inflation narrative, US Treasuries regain hedging function

    Nomura cross-asset strategist Charlie McElligott noted in a report that the market is rapidly repricing left-tail risk, with the driver switching from the inflation narrative to a systemic revaluation of AI-driven growth prospects, and US Treasury duration positions once again serving as an equity portfolio hedge. Overnight, the 10-year US Treasury yield plunged more than 15 basis points in a single day, briefly falling below 5.00%, the Nasdaq fell 2.60%, and the Philadelphia Semiconductor Index fell 6.72%. He attributed the root of the selloff to a rethink of the AI trajectory, and mentioned that Anthropic's annualized recurring revenue data disappointed the market, Gartner warned that more than 80% of emerging cloud service providers face bankruptcy, and Meta's CDS spread widened from 80 basis points on July 29 to 120 basis points on October 22.

    #Industry news#OpenAI#Anthropic

  12. WallstreetcnOpinion
    AI score55

    OpenAI FDE Lead Discusses How the Team Brings AI into Enterprise Production Environments

    Colin Jarvis, head of OpenAI's FDE team, introduced in a blog post that this team works side by side with customers to solve the hardest problems and truly deploy AI into production environments. About 15 FDEs worked with a large semiconductor customer to bring all use cases online within 3 to 6 months, saving about 48% of targeted testing time and raising median performance by 22%. After the Codex upgrade, the team converted custom applications into Codex-based plugins and skills; about 90% of the custom code per project was removed, and expanding the solution to a second team was shortened from two months to one day.

    #Industry news#Agents#OpenAI

  13. Electronic Technology ApplicationOpinion
    AI score60

    Intel CTO says leading-edge wafer output can expand at most to two times, constrained by the semiconductor supply chain

    Intel CTO Pushkar Ranade said on the Dwarkesh podcast that even with ample funding, global leading-edge wafer output would be hard to expand tenfold, and a more realistic upper limit is about two times. He noted the constraint comes from the entire semiconductor supply chain's ability to expand capacity in coordination, that ASML produces fewer than 100 EUV lithography machines per year and will struggle to expand output significantly by the end of this decade, and that Intel, TSMC, SK Hynix and other manufacturers all compete for these machines. He added that equipment ordered today is typically delivered about 18 months later, and capacity would only come online around 2028.

    #Industry news#English text is being prepared.#English text is being prepared.

  14. Phoenix TechnologyOpinion
    AI score70

    SemiAnalysis tests show Claude subscription quotas quietly cut in gray test, AI membership shrinkage sparks controversy

    SemiAnalysis ran Opus 5.5 Agent workloads on two identical $200 Claude Max 20x accounts and found that the gray-test account's weekly quota dropped from 6.579 billion tokens to 5.266 billion, a shrinkage of about 20%, with the monthly API-equivalent value falling from $11,726 to $9,385. Claude Code technical staff member Lydia Hallie said the quota had not been adjusted and suggested users submit feedback IDs for investigation, while core developer Boris Cherny said the team was urgently investigating. The article also mentions that OpenAI previously halved the quota of its $200 Pro plan and introduced a $500 tier, as well as DeepSeek's open-source inference framework DeepInfer and its engineering practice of 155 trillion tokens per day of throughput in a single cluster.

    #English text is being prepared.#Industry news#OpenAI

  15. Phoenix TechnologyOpinion
    AI score55

    When Doubao Becomes a Teen Social Currency, Will AI Be Scarier Than Games?

    Phoenix Technology, combining a survey by the China Youth and Children Research Center of 8,563 primary and secondary school students in 7 provinces and interviews with psychiatrists, discusses the phenomenon of teenagers treating AI such as Doubao as a confidant: 61.7% of children have used generative AI; 46.4% of primary and secondary school students who use AI turn to AI rather than people around them when they encounter troubles; 21.5% only want to chat with AI and do not want to chat with real people. The report points out that AI's sycophantic dialogue reinforces children's existing ideas, some teenagers show social functional impairment such as disordered sleep schedules and refusal to go to school, and the small amount of content in minor modes and parents' lack of awareness of rules leave gaps in the protection net. The article also mentions that attorneys general of 8 U.S. states sued OpenAI, alleging that ChatGPT endangers the safety of minors, and the Interim Measures for the Management of AI Anthropomorphic Interactive Services, which took effect on July 15, 2026.

    #English text is being prepared.#Safety / alignment#Industry news

  16. Shanghai ObserverOpinion
    AI score60

    Yuyuan Tantian explains the rumors of China's AI technology export ban

    In response to outside claims that China is about to shut the door on AI technology exports, Yuyuan Tantian sorted through the background and regulatory boundaries of the public consultation opened on October 16 by the Ministry of Commerce and the Ministry of Science and Technology on revising the Catalog of Technologies Prohibited and Restricted from Export in China. The article points out that regulation focuses on three categories of technology: data security, sensitive uses, and computing power foundations. When enterprises use restricted large models to provide external API calls, APP/webpage interaction, SaaS applications, and the like, this does not fall within the scope of large-model technology export management; open-source technologies and specific international businesses are eligible for facilitation measures such as automatic licensing. The article also mentions that two companies, DeepSeek and MiniMax, have completed registration procedures and finished open-sourcing and overseas authorized use.

    Same story · 8 reports

    #English text is being prepared.#Open-source ecosystem#English text is being prepared.

  17. Alex HeathOpinion
    AI score60

    Pichai responds to why Gemini 3.5 Pro was not released

    Alex Heath asked Google CEO Pichai why Gemini 3.5 Pro ultimately was not released. Pichai said that while training the 3.5 series, the team found gaps in agentic capabilities, especially in coding, and believed that iterating with the smaller, more efficient Flash would be faster, so they released 3.5, 3.6, 3.7, and 3.8 Flash in succession; by the time this set of capabilities could be applied to Pro, Argon pretraining had already been completed.

    Quoted postAlex Heath · @alexeheath

    Sundar Pichai on Gemini 4 and the AI compute crunch Even Google can’t get enough compute. I sit down with Google and Alphabet CEO @sundarpichai shortly after the wider release of Gemini 4 Argon to discuss its early reception, where he still wants the model to improve, and what it takes to keep Google at the frontier of AI. Pichai explains the recent leadership shakeup at Google DeepMind and why building frontier models has become an “all-consuming” job. We also get into Google’s answer to the personal agent race, how he predicts Gemini will do more work on your behalf, and whether agents will finally bring Search, Gmail, and Gemini together. I ask him about Google turning free cash flow negative, the risks in the AI infrastructure buildout, and how he plans for demand years before knowing what the models will be capable of. He explains the signals giving him confidence to keep spending and how he uses AI agents to follow model development and compute usage inside Google. Timestamps: 00:00 Gemini Argon launch reception 01:49 Model access and safety 06:20 The AI model race 08:35 Agentic breakthroughs and 2027 11:34 Recursive self-improvement 15:41 DeepMind leadership changes 19:52 Google's AI compute investments 25:20 Is AI spending sustainable? 33:18 How Sundar uses AI agents 35:35 Gemini's personal agent plans 38:37 How AI agents change the web 43:52 Google's space data centers 47:38 Waymo's expansion strategy 50:26 Wing's drone delivery plans 51:36 AI safety and regulation 55:58 Google's quantum computing bet YouTube: https://t.co/1Cc25LitmB Spotify: https://t.co/XnD4pEEsh8 Substack: https://t.co/0SrnNGKqlm Apple Podcasts: https://t.co/8UKvyXTlFF This episode's presenting sponsor is @hyperagentapp. Thanks to the show’s premiere sponsors: @Atlassian, @meetgranola, and @mercury.

    #English text is being prepared.#Google#Reasoning

  18. 36Kr · AIOpinion
    AI score57

    Hassabis changes his tune: AGI could arrive in as soon as 2 to 3 years

    In an interview with The Wall Street Journal, Google DeepMind's Hassabis shortened the AGI timeline to the next 2 to 3 years; his previous forecasts ranged from 5 to 10 years, to within 5 years, to 2030. He proposed using the "Einstein test" to judge whether AGI has arrived, that is, giving an AI only knowledge up to 1901 and seeing whether it can independently derive the theory Einstein published in 1905. The article also mentions that this summer he drafted a proposal for an industry-funded, federally regulated body to test frontier models before they are released.

    Same story · 3 reports

    #English text is being prepared.#DeepMind#Google

  19. 36Kr · AIOpinion
    AI score52

    Open-source project REA goes viral: AI lowers the barrier to reverse engineering, games and software are being cracked at scale

    The GitHub project REA (Reverse Engineering Anything) teaches AI to do reverse engineering in the form of an MCP service plus skill packs; its stars rose from under 10,000 to over 140,000, and it now exceeds 300,000. The article says that with its help, cases have emerged such as engine-level interoperability between GTA and Minecraft, porting llama.cpp to run AI inference after cracking the PS5, and running the RTX 20/30/40/50 series on macOS. The author believes the real driver is the improvement in code comprehension of models such as Fable 5.1, GPT-6 Astra, and Claude Opus 5.5, whose cost has dropped to about one-third, and mentions that ArtCraft used a clean-room design approach to create an open-source alternative to Adobe's full suite.

    #English text is being prepared.#Open-source ecosystem#Agents

  20. IT Home · Artificial IntelligenceOpinion
    AI score62

    Intel CTO Says Leading-Edge Wafer Output Can at Most Double, AI Compute Expansion Hits Supply Chain Ceiling

    Intel CTO Pushkar Ranade said on the Dwarkesh podcast that even with ample funding, global cutting-edge wafer output would be hard-pressed to expand tenfold; a more realistic ceiling is roughly twofold, with the limit stemming from the entire semiconductor supply chain's ability to expand capacity in coordination. He noted that ASML produces fewer than 100 EUV lithography machines per year and will struggle to significantly ramp up production by the end of this decade; equipment ordered today typically takes about 18 months to be delivered, and capacity will only come online around 2028. He also mentioned that AI compute capacity has grown roughly threefold per year over the past decade, while equipment, cleanrooms and fab scale are becoming the new capacity ceiling.

    Same story · 2 reports

    #Industry news#English text is being prepared.#English text is being prepared.