a16z multiple long-term investors in American industries, financial services, and enterprise software stated in a video released at the end of 2025 that early in 2025, OpenAI and Google almost simultaneously accelerated their deployment of consumer AI, from models to interface design, with the goal of making it easy for the general public to get started. a16z believes that the consumer AI market has already shown an early structure of "winner-takes-all or dominated by a few leading players," but as demand diversifies, the LLM market is moving toward niche segments, and startups remain key drivers in application and product experience. The starting moment of the year, the consumer AI battle begins Looking back at early 2025, OpenAI and Google almost simultaneously accelerated their investment in the consumer AI market. Whether it was launching new models, updating features, or trying out entirely new user interfaces, the direction was very clear: to enable

Information technology service company Coforge(Coforge) has acquired Encora(Encora) with a scale of approximately 3.38 trillion Korean won, accelerating its entry into the next-generation AI technology market. Coforge plans to leverage this acquisition to capitalize on Encora's AI and technological capabilities headquartered in New Jersey, USA. In particular, Encora's enterprise application development, AI-based data processing, and user interface design capabilities are regarded as core assets. Coforge has raised a bridge loan of $550 million (about 7.9 trillion Korean won) to restructure Encora's existing debt and plans to complete the transaction through an equity swap. Encora's advantage lies in its ability to provide global enterprises with technology that optimizes large language models(LLM) based on internal data, or transform them into automated agents integrated into enterprise applications. The company processes unstructured data through its proprietary platform "AIVA" and has achieved

Vitalik on Christmas Eve called Grok a "net improvement" for the X platform, highlighting a new debate on AI bias governance (Background: Musk xAI collaborates with El Salvador to launch the world's first "National AI Education Program": one million students use Grok as personal tutors) (Additional context: Musk calls on Grok to challenge the strongest human LOL team next year: if successful, it will prove a substantial breakthrough in AGI development) On Christmas night 2025, controversy in Silicon Valley flared up, with fierce clashes between left and right on social media platforms. At this most concentrated moment of information bubbles, Ethereum co-founder Vitalik Buterin rarely endorses Elon Musk's AI chatbot Grok, believing that even with frequent errors, it still injects valuable "sincerity" into the X platform.

AI Coding Platform Lovable is rewriting growth stories at an astonishing speed. This startup, founded just a year ago, has achieved an annual recurring revenue of $200 million with fewer than 100 employees, and in its recent Series B funding round, it was valued at $6.6 billion, raising $330 million. Investors include NVIDIA. Elena Verna, Head of Growth at Lovable, revealed how the company has abandoned traditional marketing doctrines and redefined growth strategies in the AI era during an exclusive interview on the well-known podcast "Lenny’s Podcast." The AI Era Requires Abandoning Old Scripts: From Optimization to Innovation Elena Verna pointed out that companies like Lovable, at the forefront of the wave in the AI era, have accumulated traditional growth over the past 15 to 20 years.

Author: Andrej Karpathy Compiled by: Tim, PANews 2025 is a year of rapid development and full of uncertainties for large language models, and we have achieved fruitful results. Below are what I personally consider noteworthy and somewhat surprising "paradigm shifts" that have changed the landscape and left a deep impression on me, at least on a conceptual level. 1. Reinforcement Learning with Verifiable Rewards (RLVR) At the beginning of 2025, the LLM production stack of all AI laboratories will roughly present the following form: Pre-training (GPT-2/3 from 2020); Supervised fine-tuning (InstructGPT from 2022); and Reinforcement Learning from Human Feedback (RLHF, 2022) For a long time, this has been a stable and mature technology stack for training production-level large language models. By 2025, reinforcement based on verifiable rewards

Social media is flooded with AI spam content, and genuine user sharing willingness is decreasing. Top venture capital firm a16z proposes the concept of staking media, using crypto asset staking mechanisms to filter AI noise with real money, and rebuild content trust through verifiable commitments. (Background summary: Animal Crossing adds AI LLM, "playability skyrockets"; streamers try it out: endless conversations without repetition) (Additional background: AI-generated games suspected of copying Pokémon! "Mythical Beast Paru" launched on Steam, selling 2 million copies; Nintendo legal team considering lawsuits?) Table of Contents When AI begins self-replication, the internet is being flooded with "pre-made content" In the era of AI proliferation, build media trust with real money Use staking mechanisms to increase the cost of fakes, and suggest introducing dual content verification mechanisms Current social media still seems lively, but the "sense of real human presence" is gradually fading

American startup Starcloud announces the successful launch of NVIDIA (NVIDIA) H100 GPU into space, and its operation of Google's open-source LLM Gemma in orbit, setting the world’s first record for "LLM execution in space." The team hopes to demonstrate that outer space has the potential to become the next-generation data center, which could help alleviate Earth's pressure on energy, land, and infrastructure. With companies like Google, Lonestar, and Aetherflux gradually investing, (Orbital Computing) has become an emerging battleground in the tech industry. Starcloud launched a space mission in November, with the H100 capable of space computing Based in Washington state, Starcloud launched the Starcloud-1 satellite in November of this year.

After taking a general look at some of the winning projects from the @solana x402 hackathon, I found that there isn’t much hype around narrative layers like Facilitator or Launchpad. Instead, most focus is clustered around service layer tools that make it easier for Agents to call payment functions: - Galaksio aims to solve the problem of on-demand access to GPU computing resources to optimize the cost of computing services; - PayPerPrompt is working on API aggregation for LLM models, allowing Agents to pay per prompt when using various models like GPT, Claude, Gemini, etc.; - Triton Gateway packages Solana’s historical data into a x402 paid API, so developers pay per query instead of running full nodes themselves; - x402

J.P. Morgan released its 2026 investment outlook report, highlighting three key themes throughout: "Artificial Intelligence (AI)," "global fragmentation," and "inflation." J.P. Morgan points out that the era of low inflation and seamless globalization has clearly come to an end. Instead, three powerful and interconnected forces are shaping a new market landscape. Together, they constitute a fundamental challenge: How should we invest when the prospects for AI-driven productivity growth are in conflict with more persistent, volatile inflation and a fragmented world order? This article will focus on summarizing the chapters related to the AI bubble. 2026 Investment Keywords: AI, Global Fragmentation, and Inflation J.P. Morgan believes that the most significant change brought by artificial intelligence is its potential to reduce the cost of professional skills to zero, describing this transformation as comparable to the rise of computer technology. This...

2 December, 2025 – Tether Data today announced the launch of QVAC Fabric LLM, a new comprehensive LLM inference runtime and fine-tuning framework that makes it possible to execute, train and personalize large language models directly on everyday hardware, including consumer GPUs, laptops, and even s

In Brief Tether Data has launched QVAC Fabric LLM framework that enables LLM inference and fine-tuning across consumer devices and multi-vendor hardware, supporting decentralized, privacy-focused, and scalable AI development. Department of Financial Services company Tether, focused on

Crypto Market Overview BTC (+0.25% | Current price 91,878 USDT): After completing its decline near $83,800, BTC began a gradual rebound on December 2, moving up to the $91,000–93,000 range, with a clearly strengthened short-term structure. In terms of moving averages, the MA5 and MA10 have quickly crossed above the MA30, forming a short-term bullish alignment, indicating that the market has entered a phase of rhythmic recovery after a sharp decline. Although the rebound is relatively steep, it has not yet broken through the resistance zone above $93,000. The price needs to consistently hold above $91,500–92,000 to consolidate the short-term bullish advantage. On December 2, the MACD showed a strong golden cross, with the red bars expanding significantly, indicating a substantial improvement in buying momentum compared to earlier. However, as it approaches the $93,000 high...

Grok, xAI’s LLM chatbot, predicts XRP price if Bitcoin ever reaches the audacious $1 billion projection from a Fidelity executive. Notably, three years ago, Fidelity’s Director of Global Macro, Jurrien Timmer, made one of the boldest Bitcoin price forecasts ever. He believed Bitcoin could reach $1

According to a report by the American technology media "The Information" on December 2, OpenAI's research head Mark Chen recently revealed in an internal company meeting that OpenAI is accelerating the development of a brand new large language model (LLM) codenamed "GARLIC." (Background: Wood's statement that "AI is not a bubble": currently replicating the wealth explosion moment of the internet) (Background information: Google officially launched "Gemini 3"! What are the highlights of becoming the world's smartest AI model?) According to an exclusive report by the American technology media "The Information" on December 2, OpenAI's research head Mark Chen recently revealed in an internal company meeting that OpenAI is accelerating the development of a brand new large language model (

Ukraine is developing its own large language model (LLM) based on Google's technology to accurately understand context, dialects, and minority languages. The project aims to create an independent AI system for military and civilian use, utilizing data from various government sources.

Fei-Fei Li, the founder of World Labs and renowned as the "AI Godmother," accepted an interview to discuss how AI needs to go beyond language and develop "spatial intelligence" so that machines can truly understand and construct the 3D physical world. (Background: a16z's former partner released a significant tech report: How AI is consuming the world?) (Context: Ray Dalio from Bridgewater: It is still too early to sell AI stocks! Because the "long wick candle" that will burst the bubble has not yet entered the scene.) At a time when large language models are sweeping the globe, Fei-Fei Li, a Stanford University professor hailed as the "AI Godmother," has already turned her attention to the next frontier of artificial intelligence: spatial intelligence. After leaving Google Cloud, Fei-Fei Li founded the highly anticipated startup World Labs and launched the first global model.

LLM cannot reliably determine the state of the real world, and AI Agents face high vulnerability at the execution level. The missing Agent Oracle is the cornerstone of the entire Agent ecosystem, yet it has been long overlooked. The essence of LLM capability is to generate the most probable text, rather than to serve as a system for inferring the truth of the world. It does not verify the authenticity of news, nor does it identify phishing links; these tasks belong to "fact-checking" rather than "language prediction."

In the past few months, while working on the Agent system, I have increasingly realized something that is severely underestimated by everyone: no matter how powerful LLM becomes, it cannot reliably assess the state of the real world. Once the Agent enters the actual execution layer—opening accounts, trading, visiting websites, submitting forms—it is exposed to a high level of vulnerability. Because it lacks a "reality layer." What we are missing is the Agent Oracle, which is almost the cornerstone of the entire Agent ecosystem but has long been overlooked. Why is LLM not enough? Because the essence of LLM's capability is to generate the most probable text, rather than being a system that infers the truth of the world. It does not verify the authenticity of news, does not recognize phishing links, does not determine whether an API is compromised, does not understand whether a regulation is truly in effect, and cannot accurately grasp the reality behind Powell's speech.

According to Mars Finance, FastX Network has completed a $3 million financing round led by IBC Group, Castrum Partner, Alpha Capital, Gemhead, and TBV Partner. FastX Network is an AI-driven decentralized prediction market that uses custom LLM models for encryption predictions and integrates real-time data, accessible via web and

Microsoft announced its Q3 2025 financial report, with revenue and profits exceeding market expectations. This quarter's revenue reached $77.67 billion, an 18% year-over-year increase, and earnings per share were $3.72. The key factor is the cloud sector, with Azure's revenue growth rate at 40%. However, to strengthen its AI and cloud capabilities, CapEx soared to $34.9 billion, setting a historical high. In addition, due to the impact of investments related to OpenAI, non-operating gains and losses decreased by $3.7 billion. Despite strong fundamentals, the accelerated capital expenditures remain the primary risk of concern for investors. (OpenAI has completed its capital restructuring and established PBC! The latest valuation is 500 billion dollars, with Microsoft holding a 27% stake) In 2025, while the entire AI industry is crazily expanding computing power, Microsoft is going against the tide. The company quietly halted the construction of some data centers, which once sparked external concerns.

The essay discusses North Korea's advanced techniques for targeting LLMs and cryptocurrencies, focusing on using PROMPTFLUX and PROMPTSTEAL for real-time attacks and expanding BIGMACHO delivery methods that threaten crypto wallets.

In the era of generative AI, the models of giants like OpenAI, Google, and Anthropic have nearly consumed all publicly available data on the web. However, research conducted by Oxford University and several institutions indicates that by 2026 to 2028, the high-quality publicly available data that humans can provide to AI will soon be depleted. When the internet is flooded with AI-generated content, new models will inevitably need to train themselves using data generated by AI. This self-referential process is akin to the inbreeding of AI's close relatives. By 2026, the data generated by humans will be learned thoroughly by AI. The University of Oxford, the University of Cambridge, and several research institutions published a paper in April 2024 titled "The Curse of Recursion: Training on Generated Data Makes Models

According to Mars Finance, the decentralized AI inference routing network DGrid AI has announced that it has received seed round investment support from institutions such as Waterdrip Capital, IoTeX, Paramita VC, Catcher VC, 4EVER Research, and Abraca Research. DGrid's core relies on the "AI RPC + LLM inference + distributed Node" architecture, aiming to break the monopoly pattern of centralized AI platforms and provide open, trustworthy, and low-cost AI capability support for the Web3 ecosystem. The financing will mainly be used for building the Node network and expanding ecological partnerships. DGrid officially stated that its Node presale plan will soon be launched, allowing community members to participate in the construction of the decentralized AI network in advance by operating Nodes and sharing the network.

AI Qwen, Alibaba's flagship large language model (LLM) series, is rapidly gaining traction as a versatile open-source, driving innovation in artificial intelligence applications.

Brevis has built an initial moat on both "performance reproducibility" and "business feasibility," constructing a general verifiable computing infrastructure centered around zero-knowledge computation. (Background: Ethereum was praised by Vitalik Buterin for Polygon in response to the recent controversy: significant contributions to ZK, not just boring finance) (Additional context: Vitalik Buterin wrote a lengthy article: the GKR cryptographic protocol can quickly prove Ethereum, zk-ML is accelerating AI LLM) Brevis has established an initial moat on both "performance reproducibility" and "business feasibility": Pico/Prism has firmly secured the top tier in the L1 RTP race, while zkCoprocessor opens up high-frequency, reusable commercial scenarios. "Off-chain computation + on-chain verification" for trusted computing (Verifiable

Tech giants are aggressively pushing generative AI, but as users' excitement turns to fatigue, the market may soon face a functional cleansing. (Background: Vitalik Buterin posts a lengthy article: GKR password protocol can quickly prove Ethereum, zk-ML is accelerating AI LLM) (Contextual note: Bitcoin miners' "valuation logic shift": the profits from powering AI far exceed mining Bitcoin) From the Metaverse to Web3, and now to generative AI, Silicon Valley has repeatedly created trends. But have you recently felt that as AI features flood into daily life, a sense of "AI fatigue" is emerging behind the hype? Many consumers are starting to feel burdened by these new features, even questioning their true value. The more AI features are pushed, the more users cry "can't keep up". Over the past year, from mobile phones, emails, and presentations to search engines, almost every update boasts generative.

According to Mars Finance, the decentralized AI reasoning network DGrid AI has announced that it has received seed round investment support from institutions such as Waterdrop Capital, IoTeX, and Paramita VC. DGrid's core relies on the "AI RPC + LLM reasoning + distributed Node" architecture, aiming to break the monopoly of centralized AI platforms and provide open, trustworthy, and low-cost AI capability support for the Web3 ecosystem. The financing will mainly be used for building the Node network and expanding ecological partners. Meanwhile, to build a truly community-driven decentralized network, DGrid officially announces that its Node presale plan will soon be officially launched. This plan will allow community members to participate in the construction of the decentralized AI network in advance by operating Nodes and share in the early growth dividends of the network. Specific rules and timing will be announced through official channels.

Vitalik Buterin posted to introduce the GKR protocol, enabling zk-SNARKs (ZKP) to operate in real-time, requiring only a small amount of GPU to process Ethereum L1, significantly improving efficiency and dropping verification costs, laying the foundation for Blockchain scalability and AI privacy computing. The concise design of GKR and the future application of ASICs indicate the accelerated growth of the Web3 ecosystem.

JPMorgan Chase is transforming into an AI-driven enterprise, showcasing a bot that can create investment banking presentations in 30 seconds. This innovation, part of their LLM Suite, aims to enhance efficiency and reduce staff while maintaining a competitive edge in finance.

A cancer-stricken streamer was maliciously updated by "BlockBlasters" to steal $32,000, highlighting the loopholes in Steam's review process and the high risks associated with encryption assets (Background: Animal Crossing introduced AI LLM, significantly increasing playability; the streamer tried it out: conversations last a lifetime without repetition) (Additional context: A beautiful streamer played "Black Myth: Wukong" using brainwaves to fight against a white-clothed swordsman, sparking discussions across the internet) The cancer-stricken streamer RastalandTV (real name Raivo Plavnieks) opened the Steam game "BlockBlasters" during a live broadcast to raise funds for his fourth round of cancer treatment costs, and within just a few minutes, the Wallet that originally held through.

When AI can optimize everything, the only thing that matters is understanding how the various elements in the strategy are interconnected. π-type marketing talents will become the trend of the future. This article is sourced from a piece by Rosie, organized, compiled, and written by Forsight News. (Background: The first batch of post-00s Web3 workers has already begun to "leave the circle") (Additional background: Bill Gates: AI will replace humans in 10 years, working two days a week is not a dream, three professions may survive) The industry has undergone tremendous changes in the past five years. The traditional concept of "T-shaped marketers" has vanished, crushed by artificial intelligence, automation, and many other factors. If you still believe that a depth skill + broad knowledge = job security, then you are more likely to be replaced by large language models (LLM) in the next 5 to 10 years. This is not at all.

OpenAI released a new research paper, stating that even though large language models (LLM) like GPT-5 have made significant progress, "AI hallucinations" (Hallucinations) remain a fundamental problem that may never be completely eliminated. The research team revealed through experiments that the model can confidently provide entirely incorrect answers when responding to specific questions, and proposed a new "evaluation mechanism" reform plan aimed at reducing the model's tendency to "guess randomly." Researchers tested the AI model with different questions, and all the answers were wrong. Researchers asked a widely used chatbot about a certain doctoral thesis title, and received three consecutive answers that were all incorrect. Then they asked about his birthday, and the chatbot similarly provided three different dates, all of which were incorrect. Research indicates that AI models can be very effective when confronted with "rare information" in certain datasets.

????AI is far more than LLM! Musk boldly claims in the latest ultimate AI plan that 80% of Tesla's value in the future will come from Bots! With the concept stocks of Bots rising one after another, Web3 Bots projects are also accelerating to ignite a new wave of enthusiasm. How will the smart ecosystem of Decentralization and on-chain collaboration reshape our future? Follow Biteye to unlock the new star in the Web3 Bots track! 1. @openmind\_agi Keywords: Operating System, Decentralization Coordination Layer OpenMind raised $20 million in funding, hoping to enhance the understanding and learning abilities of Bots through an open-source system, with its main products including: OM1: AI native operating system, known as "the Android system for Bots," hardware-agnostic and open source. It can endow machines with the abilities of perception, memory, planning, and control, assisting Bots in reasoning.

AI is far more than LLM! In his latest ultimate AI plan, Musk boldly claims that 80% of future value will come from Bots! With a wave of big pumps in the concept stocks of Bots, Web3 Bots projects are also accelerating to ignite the trend. How will the decentralized, on-chain harmonious intelligent ecosystem dominate our future? Following Biteye, let's unlock the new stars on Web3 Bots together! 1. @openmind\_agi Keywords: Operating System, Decentralization Coordination Layer OpenMind raised $20 million in funding, aiming to enhance the understanding and learning capabilities of Bots through an open-source system. Its main products include: OM1: An AI-native operating system, known as the "Android system for Bots", hardware-agnostic and open-source. It empowers machines with the capabilities of perception, memory, planning, and control, assisting Bots in understanding the world and taking relevant actions based on context. Previously

The new idol of young people, Wai Wai Meng Meng, has published a book teaching you how to play with AI. Waiwai Mengmeng is a well-known internet celebrity and singer-songwriter in Taiwan. The single "Wai Meng's 300 Days Gift" has over 140,000 views on Youtube. The main creator is Mengbao Mengbert, a graduate of the Civil Engineering Department at National Taiwan University, who is currently studying in the Music Department's graduate program at Fu Jen Catholic University. The one publishing this book is Weibao Weibert, who holds a Master's degree in Computer Science from National Taipei University and has won the Ministry of Education's National Higher Education Artificial Intelligence Competition AI CUP Gold Medal and the Trend Micro Student Pre-Employment Award. This time he published a book under the pen name "好崴寶(Weibert Weiberson)", combining theory and practice, and launched the "Local End Ollama × LangChain × LangGraph × LangSmith Development Manual: Creating

Nano gained 3.09% but faced thin liquidity, with trading volume down 17.05%, showing weaker support behind its upward momentum. The Large Language Model slipped 0.99% despite high turnover, as its fully issued supply leaves price movement tied only to demand. Celium rose 1.7% but revealed liquidit

The Kaggle AI International Chess Tournament has concluded, with the untrained o3 achieving a 4-0 shutout victory over Grok 4, demonstrating strong reasoning abilities. (Background: Musk threatened to sue Apple: The App Store ranking shows monopolistic behavior, maliciously suppressing Grok) (Additional background: Grok 4 is now available for free use, Musk's xAI is in direct competition with GPT-5) Recently, on August 14, Google-owned Kaggle announced the results of the "AI Chess Exhibition Match," where OpenAI's general large language model o3 swept xAI's Grok 4 with a score of 4:0, winning the championship and becoming the first LLM to shut out an opponent without specialized training. A total of 8 AI participated in the event, which lasted three days and was decided through a knockout format. Language model.

HomeNews Theta Labs launches an LLM (large language model) inference service on EdgeCloud with distributed, blockchain-based verifiability. The update enables independently verified and tamper-proof AI chatbot outputs by integrating public randomness from the blockchain. EdgeCloud is now the

As AI models become increasingly powerful, people are starting to worry whether they will have their own "malicious intentions." Anthropic has released the SHADE-Arena evaluation framework to test whether large language model (LLM) has the capability to secretly execute unauthorized destructive actions by users while seemingly completing legitimate tasks, and the results were unexpected. (Is GPT becoming a bit strange? Three major events reveal the potential out-of-control risks of AI) Will AI secretly cause damage? SHADE-Arena provides an experimental answer. SHADE-Arena ( Subtle Harmful Agent Detection & Evaluation ) is a simulated working environment that allows AI models to perform daily tasks while testing whether they can also complete a covert malicious sub-task. For example

1. Introduction to Kaito Kaito is a Web3 information platform dedicated to solving the problem of information fragmentation in the crypto world. It collects and organizes real-time data from various sources such as social media, research forums, podcasts, etc. through the AI-driven Kaito Pro search engine and Kaito Connect InfoFi network. The platform utilizes large language models (LLM) and semantic understanding technology to convert unstructured information into instant insights, including sentiment analysis, keyword tracking, narrative context mining, and other functions. In addition, Kaito Yaps allows users to

HomeNews Researchers have identified a new method called TokenBreak that bypasses large language model (LLM) safety and moderation by altering a single character in text inputs. The attack targets the way LLMs break down text (tokenization), causing safety filters to

World Labs is a startup founded in 2024 by renowned AI expert and Stanford University professor Fei-Fei Li, dedicated to developing the next generation of AI systems with "spatial intelligence." Since its establishment, World Labs has completed two rounds of financing, raising a total of approximately $230 million. Major investors include a16z, Radical Ventures, NEA, NVIDIA NVentures, AMD Ventures, and Intel Capital. The company's valuation surpassed $1 billion in just three months, making it a new unicorn in the AI field. Recently, Fei-Fei Li met with a16z partners Martin Casado and Eric.

In a significant advancement for Web3 innovation, ChainGPT announced a strategic partnership alongside Alibaba Cloud, one of the biggest and most reputable cloud service providers in the world. The goal of this collaboration is to advance the boundaries of AI and blockchain, specifically in regard t

According to Deep Tide TechFlow news, on May 7th, the Metis AI high-performance chain Hyperion Testnet officially went live last night at midnight China time. Hyperion is a high-performance, AI-optimized Layer 2 solution designed specifically for AI, DePIN, DeFi, and GameFi. It expands the Metis ecosystem through parallel execution, decentralized ordering, and AI-native infrastructure, while maintaining Ethereum's security and using METIS as the Gas token. Hyperion is developed based on the Metis SDK, redefining Layer 2 scalability through MetisVM, MetisDB, and the combination of Optimism Rollup technology and parallel transaction execution. The Metis SDK integrates LazAI-developed A

The article discusses the launch of DeepSeek R1 and its impact on responsible innovation and Risk Management. DeepSeek R1 has developed a large language model (LLM) and achieved success, but still has privacy and security vulnerabilities. The article reminds developers to return to basics and innovate responsibly, while emphasizing the need for careful implementation of thorough Risk Management before using AI systems. The release of DeepSeek has also raised issues related to data privacy, security, and censorship. The article suggests considering the development of decentralized AI and calls for the establishment of unified global AI regulations.

Press Release FLock.io, the private AI training platform, has announced a collaboration with Alibaba Cloud, the digital technology and intelligence backbone of Alibaba Group, to harness Alibaba Cloud's Large Language Model(LLM) Qwen and cloud technologies to create advanced AI models for both

This article compiles the verbatim transcript of a public conversation between Meta's Chief AI Scientist and Turing Award winner Yann LeCun and NVIDIA's Chief Scientist Bill Dally. LeCun explains why he believes that large language models (LLM) can never truly achieve AGI. (Background: OpenAI released the strongest reasoning models o3 and o4-mini: capable of thinking about images, automatically selecting tools, and breaking through in math and coding performance.) (Supplementary background: OpenAI is secretly building its "own community platform" targeting its rival Musk's X.) As large language models (LLM) accelerate the world's embrace of AI, Yann LeCun, hailed as the father of convolutional neural networks and current Chief AI Scientist at Meta, recently made astonishing remarks.

This article is based on a public conversation between Yann LeCun, Chief AI Scientist at Meta and Turing Award winner, and Bill Dally, Chief Scientist at NVIDIA. LeCun believes that the craze for large language models (LLM) is nearing its end, and future breakthroughs in AI will lie in understanding the physical world, reasoning, planning, and Open Source models. (Background: OpenAI released o3 and o4-mini, the most powerful reasoning models: capable of thinking about images, automatically selecting tools, and achieving breakthroughs in mathematics and coding performance.) (Additional context: OpenAI is rumored to be secretly building its own social platform, targeting its arch-rival Musk's X.) In today's world, where the AI wave is sweeping across the globe, while everyone's attention is still focused on the latest developments of large language models (LLM), the father of convolutional neural networks and current Chief AI Scientist at Meta,

Google successfully cracked down on fraudulent ads by importing large language model (LLM) and a panel of experts. Nearly 40 million ad accounts have been halted last year, more than three times more than the year before. The expert team assisted in the analysis and development of countermeasures, technical measures and policy updates, and successfully suspended a large number of suspicious ad accounts, particularly involving Deep Fake scam ads. India has also suffered from a massive ad blocking campaign, with Google emphasizing fair enforcement and providing avenues for appeal.

AI artificial intelligence is sweeping the world at an accelerated pace, with major LLM giants updating their models every few months, and various applications blooming. This article organizes the current top 10 AI application trends for you. Derived from an article by 0xJeff, organized, compiled, and authored by PAnews. (Previous summary: GPT-5 delayed! OpenAI first launches o3, o4-Mini, Sam Altman reveals: integration is harder than expected) (Background information: Moody's analysis: Trump's tariffs will kill "5.5 million job opportunities"; combined with AI destroying the U.S. economy) 1. The Trump administration uses artificial intelligence to formulate tariff formulas How to calculate tariffs to balance the U.S. trade deficit? The chatbot suggests dividing the trade deficit by imports, which seems to be the approach taken by the White House. 2. Everything can be Ghibli Now everyone uses