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  • Astro Bot wins the top prize at the New York Game Awards 2025
    venturebeat.com
    Astro Bot takes home another Game of the Year award at the New York Game Awards, along with two other trophies.Read More
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  • Founder Ted Price retires from Insomniac Games
    venturebeat.com
    Ted Price, the founder and CEO of Insomniac Games, has announced he will retire after more than 30 years with the company on March 2025.Read More
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  • OpenAI Stargate is a $500B bet: Americas AI Manhattan Project or costly dead end?
    venturebeat.com
    OpenAI, Oracle, Softbank and MGX are investing a record amount in new AI infrastructure even as China's DeepSeek outperforms on cost.Read More
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  • DeepMinds new inference-time scaling technique improves planning accuracy in LLMs
    venturebeat.com
    With "Mind Evolution" LLMs can use search and genetic algorithms to generate and combine different solutions and find the optimal one.Read More
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  • How Harness is harnessing agentic AI to help improve enterprise incident response with automated data collection and playbooks
    venturebeat.com
    The software development vendor now offers agentic AI-powered incident response that could dramatically minimize downtime.Read More
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  • Adam Boyes launches Vivrato consultancy to help manage big game problems
    venturebeat.com
    AdamBoyeshas launchedVivrato, an advisory company dedicated to forging a more collaborative, sustainable, and thriving gaming future.Read More
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  • Berkeley SkyDeck teams with Mayfield to support AI-focused student entrepreneurs
    venturebeat.com
    Berkeley SkyDeck, the global hub for entrepreneurship and accelerator, along withUC Berkeley College of Computing, Data Science, and Society(CDSS), announced a partnership withMayfield. The aims isto support AI-focused, student entrepreneurs with unparalleled access to venture capital and world-class mentorship. Part of the Mayfield AI Garage iRead More
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  • Perplexity launches Sonar API, taking aim at Google and OpenAI with real-time AI search
    venturebeat.com
    Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn MorePerplexity has launched an aggressive bid to capture the enterprise AI search market, unveiling Sonar, an API service that outperforms offerings from Google, OpenAI and Anthropic on key benchmarks while also undercutting their prices.The move signals a significant shift in the AI landscape, as Perplexity now valued at $9 billion directly challenges larger competitors by making its real-time, web-connected search capabilities available to developers and enterprises.The companys dual-tier strategy offering both a lightweight Sonar service and a more robust Sonar Pro version targets different segments of the growing AI integration market.Perplexitys Sonar Pro outperforms major AI competitors in the SimpleQA benchmark, which measures response accuracy. (Credit: Perplexity)Sonars real-time advantage: Bringing fresh data to enterprisesZoom has already integrated Sonar into its AI Companion 2.0 product, allowing users to access real-time information without leaving video conferences a capability that could reshape how businesses conduct remote meetings and research.The pricing structure appears to be designed to disrupt the market. Sonars base tier costs $5 per 1,000 searches plus minimal token fees, while Sonar Pro, despite higher token costs, offers doubled citation density and multi-search capabilities for complex queries.What sets Sonar apart is its real-time web connection, a feature absent in many competing APIs that rely solely on training data. This approach could prove particularly valuable for enterprises requiring current information, although it may face challenges in applications requiring deterministic outputs.Perplexitys two-tier API offering shows the feature differences between Sonar Pro (left) and the base Sonar service (right), with Pro featuring enhanced citation capability and support for complex queries. (Credit: Perplexity)Disruptive pricing: Affordable AI search for the enterprise marketThe launch comes at a pivotal moment in the AI industry, when companies are increasingly seeking ways to integrate AI search capabilities into their products. With recent benchmarks showing Sonar Pro achieving an 85.8 F-score on the SimpleQA benchmark significantly outperforming GPT-4o and Claude Perplexity appears positioned to capitalize on growing enterprise demand for accurate, citation-backed AI responses.The timing of this launch comes as Perplexity demonstrates significant market momentum, having just secured a $500 million funding round led by Institutional Venture Partners, which valued the company at $9 billion. This strategy could prove particularly effective as enterprises increasingly prioritize AI tools that provide verifiable, current information over black-box solutions.For technical decision makers, Sonars launch represents a new option in the AI toolkit, particularly for applications requiring real-time information access and citation tracking. However, the true test will be whether Perplexity can maintain its performance edge and pricing advantage as larger competitors inevitably adjust their strategies.Daily insights on business use cases with VB DailyIf you want to impress your boss, VB Daily has you covered. We give you the inside scoop on what companies are doing with generative AI, from regulatory shifts to practical deployments, so you can share insights for maximum ROI.Read our Privacy PolicyThanks for subscribing. Check out more VB newsletters here.An error occured.
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  • Funding for gaming startups dropped off in Q4 2024 | Konvoy
    venturebeat.com
    Konvoy's latest report shows that funding for gaming-related startups was curiously low in Q4 2024, as were VC deals.Read More
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  • How Axis Security is using Xpander.AIs agent platform to supercharge customer support ticket management
    venturebeat.com
    Through its partnership with Xpander.AI, Axis has managed to save thousands of hours monthly and grow its team sustainably.Read More
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  • Tencent introduces Hunyuan3D 2.0, AI that speeds up 3D design from days to seconds
    venturebeat.com
    Tencent's Hunyuan3D 2.0 transforms images into detailed 3D models in seconds. This could reshape how industries create virtual content.Read More
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  • More developers are making VR software for Apple visionOS than PlayStation VR2
    venturebeat.com
    The Apple Vision Pro is looking likely to see more software than the PlayStation VR2, according to a game developer survey.Read More
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  • Blockchain gaming grows to 7.4M active wallets in 2024, up 421% | DappRadar
    venturebeat.com
    Blockchain gaming reached 7.4 million daily Unique Active Wallets (dUAW) in 2024, marking 421% growth from a year ago, DappRadar said.Read More
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  • GDC survey reveals a rocky year of layoffs and AI skepticism for game developers
    venturebeat.com
    The 2025 GDC survey revealed the impact of industry-wide layoffs in 2024 where one of every 11 game developers lost a job.Read More
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  • GDC 2025 event will celebrate how games connect the world
    venturebeat.com
    UBM TechWeb unveiled the 39th edition of the Game Developers Conference (GDC) that will take place from March17 to to March 21 in SF.Read More
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  • TON becomes the exclusive blockchain for Telegrams mini-app platform
    venturebeat.com
    The Open Network Foundation, a non-profit supporting the TON blockchain community, has become the exclusive partner for Telegrams mini-app platform.As an expansion of its partnership with Telegram Messenger, TON will become the exclusive blockchain infrastructure powering Telegrams mini app ecosystem and support Telegrams global user base of over 950 million monthly active users.Since the foundation and Telegram announced their joint initiative in 2023, the TON ecosystem has experienced unprecedented growth and widespread adoption. Since then, TON has worked with Telegrams updates to its mini app platform and the use of Toncoin for pay-ins and payouts. And Telegrams advertising platform played a significant role in the growth of TONs network. The new exclusivity agreement deepens the technological ties between TON and Telegram.Unifying on-chain user experience through TON ConnectCentral to this collaboration is adopting TONs wallet connect protocol, TON Connect, as the exclusive protocol for linking Telegram mini apps to blockchain wallets.This initiative provides a simplified user experience where all Web3 mini apps in Telegram will use TON to connect and authorize blockchain transactions. All mini apps utilizing blockchain in any capacity, including custodial and non-custodial wallets, user authorization, on-chain signatures, and the sending and receiving of blockchain-based assets, must implement TON Connect as their exclusive wallet connect protocol in the next month.TON blockchain and Toncoin become exclusive for TelegramFurthermore, Telegram will continue to accept Toncoin as the only cryptocurrency for non-fiat payments made for the assets and services offered by its platform, including Telegram Stars, Telegram Premium, Telegram Ads, and Telegram Gateway, a platform alternative to traditional SMS verification. Additionally, Toncoin will be the only currency used to pay Telegram Mini App developers and channel owners for their earned Telegram Stars and advertisement revenue.Tokenization of digital assets from Telegram platformTelegram plans to tokenize digital assets exclusively on TON Blockchain within the platform, including emojis and stickers, among other digital assets, while also tokenizing limited edition gifts as NFTs.After laying foundational groundwork over the last years, TON is now ready for explosive growth in 2025. The re-energized, deepened, and exclusive partnership with Telegram is an important step in our roadmap, said Manuel Stotz, president of The Open Network Foundation, in a statement. Telegram is the sixth most downloaded app in the world, a beacon for free speech, and the default messaging platform for the global blockchain community. No other blockchain has a comparable distribution vector. As TON continues its global expansion, we reiterate our ambition to empower over 500 million users before the end of the decade.Developers are encouraged to begin the migration process to ensure a seamless transition and avoid user service interruptions. Those who migrate within Telegrams deadline will receive additional benefits from the TON Foundation, including promotional support. Detailed guidelines and FAQ for developers are available here.TON will drive Telegram mini apps.The Open Network Foundation (TON Foundation) is a non-profit organization supported by community contributors to further TONs objectives. Founded in Switzerland in 2023, TON Foundation brings together a diverse range of expertise to support protocol development, help shape the platform, and facilitate ecosystem growth. While an advocate of TONs mission, the foundation does not exercise any authority over TON. TON operates on open-source software, welcomes input and contributions from all individuals, and remains independent of central control.Asked about gaming, Stotz said in a message to GamesBeat, This agreement is significant for gaming on Telegram as it unifies the user experience by standardizing wallet connections. By utilizingTONConnect, weve eliminated the complexities involved with connecting and integrating multiple wallet solutions for gamers and developers. New crypto gamers benefit from the smoother onboarding process of a single, user-friendly interface. For developers, integration becomes much more manageable as they no longer need to accommodate a wide variety of niche wallets. At the end of the day, we want to make entry easier for gamers, and this agreement does just that.Daily insights on business use cases with VB DailyIf you want to impress your boss, VB Daily has you covered. We give you the inside scoop on what companies are doing with generative AI, from regulatory shifts to practical deployments, so you can share insights for maximum ROI.Read our Privacy PolicyThanks for subscribing. Check out more VB newsletters here.An error occured.
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  • Moku unveils Tama Meme fair-launch token launchpad on Ronin
    venturebeat.com
    Moku has unveiled Tama Meme, the first fair-launch token launchpad on Sky Mavis' Ronin blockchain network.Read More
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  • Jeonghee JJ Jeong aims to build the Americas at NCSoft as she did at Pearl Abyss
    venturebeat.com
    Jeonghee JJ Jin spent a lot of time growing the business of Pearl Abyss in the Americas, as she headed Pearl Abyss America for almost eight years.Read More
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  • X Games will test AI from Google Cloud for judging snowboarding competitions
    venturebeat.com
    Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn MoreMaking its debut in Aspen, X Games will leverage AI technology from Google Cloud to enhance objectivity in subjectively judged sports.The aim is to deepen fan engagement, and provide valuable insights that resonate with both fans and athletes, said Jeremy Bloom, CEO of X Games and a veteran of the sports business, in an interview with GamesBeat.X Games will debut a new experimental AI technology developed in collaboration with Google Cloud, during the Superpipe competition at X Games Aspen 2025,with a goal of bringing new insights and a deeper level of engagement to fans. The event from January 23 to January 25 is sold out and will see tens of thousand of people, with billions of impressions across social, web sites and linear partners. The tech will debut at an event on Thursday at the X Games in Aspen. One of the human leaders among the X Games judges was part of the team to implement it. The first thing it will do is watch practice and well ask it to predict who the top three will be among the snowboarders, Bloom said. Its also going to take over everything for free riders, and it will commentate the entire run and draw back on the history of the athlete.X Games CEO Jeremy Bloom.Bloom said the sport has a global fan base and it will share the commentary in multiple languages like Japanese. After that, it will judge the athletes based on a score. The x Games medals wont be given out based on that AI score in this particular X Games in part because the tech is so new and it isnt necessarily perfect yet, Bloom said. But you will be able to see how the AI judge compares to the human judges. Were excited to show it and preview it and show the power of the things that it does, Bloom said. I think its the future of sports.Its built on Googles Vortex large language model. Bloom said it is good at doing the things you ask it to do and you can train it on footage of events, like what a good landing looks like versus on excellent landing. Bloom said the aim isnt to replace human judges but to bring more accuracy, fairness and transparency to what has to date been a purely human subjective process. Its like the use of instant replay by basketball referees, but in the case of snow sports, no such technology is used. Its all based on what a human judge sees in the moment of the competition. X Games Aspen will have AI judges alongside human judges.You have to make sure it knows every trick in snowboarding, Bloom said. Understanding economy of motion looks like is a difficult problem.The AI technology aims to explore the potential for enhancing objectivity in judged sports, increasing fan engagement, and providing athletes with additional insights into their performances.It will analyze the mens and womens Superpipe competition event. The men compete on Thursday and Saturday. As X Games celebrates its 30th anniversary, the introduction of this technology represents a step toward exploring how emerging technologies like artificial intelligence might complement human judges and offer fans a more detailed understanding of the competition.It will watch qualifying rounds and make a judgement that will be shown to the crowd and the live event after a certain time delay. The crowd will see the results from human judges. The event has snowboarding and skiing for both men and women, with a total of 18 different events. Ive had this idea in my head for decades, Bloom said. With the technology that we have at our disposal, mistakes (in judging) should never happen. It was shaped by my two decades as a professional athlete.Bloom said the tech is cutting edge and it will bring a lot of transparency and fairness to judging. uI dont think this would have been possible last year, he said. Its showing up in ways that surprise me. Athletes say its like having a coach in a pocket.How It WorksX Games 2025 will use AI judging for snowboarding Superpipe competitions.X Games AI uses Google Clouds tools, including Vertex AI and advanced large language models, to analyze video footage and capture data on metrics such as airtime, trick difficulty, and execution. The system is designed to provide deeper analysis of each run, offering fans additional layers of understanding. The tech was developed with input from X Games judges, athletes, and analysts to ensure alignment with the competitions needs.This is just the beginning, said Bloom. AI is still in its early development when applied to action sports, but Im blown away by what our model can already do. Aspen will allow us to test its capabilities and explore how it might enhance transparency, fairness, and engagement for fans and athletes alike.Part of Broader ChangesX Games has a deal with Google Cloud.The introduction of X Games AI aligns with X Games ongoing efforts to evolve its competitions. In 2026, the Action Sports Games League (XGL) will launch a new team-based format, where athletes can compete for both individual and team recognition. The league will also include interactive features such as fantasy sports, betting, real-time analytics, and expanded opportunities for fan engagement.While X Games AI is an early experiment, it reflects our commitment to exploring ways to improve competition and fan experiences, added Bloom. We look forward to gathering feedback from its debut in Aspen and refining the technology based on those insights.X Games Aspen 2025 will provide an opportunity to evaluate the tools performance and gather input from stakeholders. Further updates on X Games AI and its potential applications are expected in the coming months.Jeff Moorad, CEO of MSP Sports Capital, said in a statement, When we acquiredXGames, our goal was to reimagine unique fan experiences and increase access to the worlds premiere athletes. TheXGamespartnership withGoogleis a great example of how we intend to use technology to enhance that experience.Daily insights on business use cases with VB DailyIf you want to impress your boss, VB Daily has you covered. We give you the inside scoop on what companies are doing with generative AI, from regulatory shifts to practical deployments, so you can share insights for maximum ROI.Read our Privacy PolicyThanks for subscribing. Check out more VB newsletters here.An error occured.
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  • Smithsonian and others will use Filecoin to safeguard digital culture heritage
    venturebeat.com
    Filecoin Foundation is stepping up today to preserve cultural artifacts in digital form using its decentralized network technology.Read More
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  • Open-source DeepSeek-R1 uses pure reinforcement learning to match OpenAI o1 at 95% less cost
    venturebeat.com
    Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn MoreChinese AI startup DeepSeek, known for challenging leading AI vendors with open-source technologies, just dropped another bombshell: a new open reasoning LLM called DeepSeek-R1.Based on the recently introduced DeepSeek V3 mixture-of-experts model, DeepSeek-R1 matches the performance of o1, OpenAIs frontier reasoning LLM, across math, coding and reasoning tasks. The best part? It does this at a much more tempting cost, proving to be 90-95% more affordable than the latter.The release marks a major leap forward in the open-source arena. It showcases that open models are further closing the gap with closed commercial models in the race to artificial general intelligence (AGI). To show the prowess of its work, DeepSeek also used R1 to distill six Llama and Qwen models, taking their performance to new levels. In one case, the distilled version of Qwen-1.5B outperformed much bigger models, GPT-4o and Claude 3.5 Sonnet, in select math benchmarks.These distilled models, along with the main R1, have been open-sourced and are available on Hugging Face under an MIT license.What does DeepSeek-R1 bring to the table?The focus is sharpening on artificial general intelligence (AGI), a level of AI that can perform intellectual tasks like humans. A lot of teams are doubling down on enhancing models reasoning capabilities. OpenAI made the first notable move in the domain with its o1 model, which uses a chain-of-thought reasoning process to tackle a problem. Through RL (reinforcement learning, or reward-driven optimization), o1 learns to hone its chain of thought and refine the strategies it uses ultimately learning to recognize and correct its mistakes, or try new approaches when the current ones arent working.Now, continuing the work in this direction, DeepSeek has released DeepSeek-R1, which uses a combination of RL and supervised fine-tuning to handle complex reasoning tasks and match the performance of o1.When tested, DeepSeek-R1 scored 79.8% on AIME 2024 mathematics tests and 97.3% on MATH-500. It also achieved a 2,029 rating on Codeforces better than 96.3% of human programmers. In contrast, o1-1217 scored 79.2%, 96.4% and 96.6% respectively on these benchmarks.It also demonstrated strong general knowledge, with 90.8% accuracy on MMLU, just behind o1s 91.8%.Performance of DeepSeek-R1 vs OpenAI o1 and o1-miniThe training pipelineDeepSeek-R1s reasoning performance marks a big win for the Chinese startup in the US-dominated AI space, especially as the entire work is open-source, including how the company trained the whole thing.However, the work isnt as straightforward as it sounds.According to the paper describing the research, DeepSeek-R1 was developed as an enhanced version of DeepSeek-R1-Zero a breakthrough model trained solely from reinforcement learning.The company first used DeepSeek-V3-base as the base model, developing its reasoning capabilities without employing supervised data, essentially focusing only on its self-evolution through a pure RL-based trial-and-error process. Developed intrinsically from the work, this ability ensures the model can solve increasingly complex reasoning tasks by leveraging extended test-time computation to explore and refine its thought processes in greater depth.During training, DeepSeek-R1-Zero naturally emerged with numerous powerful and interesting reasoning behaviors, the researchers note in the paper. After thousands of RL steps, DeepSeek-R1-Zero exhibits super performance on reasoning benchmarks. For instance, the pass@1 score on AIME 2024 increases from 15.6% to 71.0%, and with majority voting, the score further improves to 86.7%, matching the performance of OpenAI-o1-0912. However, despite showing improved performance, including behaviors like reflection and exploration of alternatives, the initial model did show some problems, including poor readability and language mixing. To fix this, the company built on the work done for R1-Zero, using a multi-stage approach combining both supervised learning and reinforcement learning, and thus came up with the enhanced R1 model.Specifically, we begin by collecting thousands of cold-start data to fine-tune the DeepSeek-V3-Base model, the researchers explained. Following this, we perform reasoning-oriented RL like DeepSeek-R1- Zero. Upon nearing convergence in the RL process, we create new SFT data through rejection sampling on the RL checkpoint, combined with supervised data from DeepSeek-V3 in domains such as writing, factual QA, and self-cognition, and then retrain the DeepSeek-V3-Base model. After fine-tuning with the new data, the checkpoint undergoes an additional RL process, taking into account prompts from all scenarios. After these steps, we obtained a checkpoint referred to as DeepSeek-R1, which achieves performance on par with OpenAI-o1-1217. Far more affordable than o1In addition to enhanced performance that nearly matches OpenAIs o1 across benchmarks, the new DeepSeek-R1 is also very affordable. Specifically, where OpenAI o1 costs $15 per million input tokens and $60 per million output tokens, DeepSeek Reasoner, which is based on the R1 model, costs $0.55 per million input and $2.19 per million output tokens.The model can be tested as DeepThink on the DeepSeek chat platform, which is similar to ChatGPT. Interested users can access the model weights and code repository via Hugging Face, under an MIT license, or can go with the API for direct integration.Daily insights on business use cases with VB DailyIf you want to impress your boss, VB Daily has you covered. We give you the inside scoop on what companies are doing with generative AI, from regulatory shifts to practical deployments, so you can share insights for maximum ROI.Read our Privacy PolicyThanks for subscribing. Check out more VB newsletters here.An error occured.
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  • Sci-fi author Alan Dean Foster moves into gaming with Pomme studio deal for Midworld exclusive
    venturebeat.com
    Best-selling sci-fi author Alan Dean Foster is moving into gaming in a multi-license deal with studio Pomme, starting with a game based on his Midworld novel.Read More
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  • Hamilton raises $1.7M to tokenize real-world assets on Bitcoin
    venturebeat.com
    Hamilton, a protocol specializing in tokenizing real-world assets (RWA) on Bitcoin, has raised a $1.7 million pre-seed funding round.Read More
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  • AI comes alive: From bartenders to surgical aides to puppies, tomorrows robots are on their way
    venturebeat.com
    Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn MoreHumanoid robots are no longer the stuff of science fiction. Imagine a world where robots not only collaborate with us in factories but also greet us in stores, aid in surgeries and care for our loved ones. With Tesla planning to deploy thousands of Optimus robots by 2026, the age of humanoid robots is closer than we think.This vision is becoming increasingly tangible as more companies showcase groundbreaking innovations. The 2025 Consumer Electronics Show (CES) showcased several examples of how robotics is advancing in both functionality and human-centric design. These included ADAM the robot bartender from Richtech Robotics, which mixes more than 50 types of drinks and interacts with customers, and Tombot Inc.s puppy dogs that wag their tails and make sounds designed to comfort older adults with dementia. While there may be a market for these and other robots on display at the show, it is still early days for broad deployment of this type of robotic technology.Nevertheless, real technological progress is being made in the field. Increasingly, this includes humanoid robots that use generative AI to create more human-like abilities enabling robots to learn, sense and act in complex environments. From Optimus by Tesla to Aria from Realbotix, the next decade will see a proliferation of humanoid robots.A conversation with Aria. Source: CNET https://youtu.be/2HQ84TVcbMwDespite these promising advancements, some experts caution that achieving fully human-like capabilities is still a distant goal. Citing shortcomings in current technology, Yann LeCun one of the Godfathers of AI argued recently that AI systems do not have the capacity toplan, reason or understand the physical world. He added that we cannot build smart enough robots today because we cant get them to be smart enough.LeCun might be correct, although that doesnt mean we will not soon see more humanoid robots. Elon Musk recently said that Tesla will produce several thousand Optimus units in 2025 and that he expects to ship 50,000 to 100,000 of them in 2026. That is a dramatic increase from the handful that exist today performing circumscribed functions. Of course, Musk has been known to get his timelines wrong, such as when he said in 2016 that fully autonomous driving would be achieved within two years.Nevertheless, it seems clear that significant advances are being made with humanoid robots. Tesla is not alone in pursuing this goal, as other companies including Agility Robotics, Boston Dynamics and Figure AI are among the leaders in the humanoid robotic field.Business Insider recently had a conversation with Agility Robotics CEO Peggy Johnson, who said it would soon be very normal for humanoid robotsto become coworkers with humans across a variety of workplaces. Last month, Figure announced in a LinkedIn post: We delivered F.02 humanoid robots to our commercial client, and theyre currently hard at work. With significant backing from major investors including Microsoft and Nvidia, Figure will provide fierce competition for the humanoid robot market.Figure 02 humanoid robots at work in a BMW factory. Source: YouTube: https://youtu.be/WlUFoZstcWgCreating a world viewLeCun did have a point, however, as more advances are required before robots have more complete human capabilities. It is simpler to move parts in a factory than to navigate dynamic, complex environments.The current generation of robots face three key challenges: processing visual information quickly enough to react in real-time; understanding the subtle cues in human behavior; and adapting to unexpected changes in their environment. Most humanoid robots today are dependent on cloud computing and the resulting network latency can make simple tasks like picking up an object difficult.One company working to overcome current robotics limitations is startup World Labs, founded by AI Godmother Fei Fei Li. Speaking with Wired, Li said: The physical world for computers is seen through cameras, and the computer brain behind the cameras. Turning that vision into reasoning, generation and eventual interaction involves understanding the physical structure, the physical dynamics of the physical world. And that technology is called spatial intelligence.Gen AI powers spatial intelligence by helping robots map their surroundings in real-time, much like humans do, predicting how objects might move or change. Such advancements are crucial for creating autonomous humanoid robots capable of navigating complex, real-world scenarios with the adaptability and decision-making skills needed for success.While spatial intelligence relies on real-time data to build mental maps of the environment, another approach is to help the humanoid robot infer the real world from a single still image. As explained in a pre-published paper, Generative World Explorer (GenEx) uses AI to create a detailed virtual world from a single image, mimicking how humans make inferences about their surroundings. While still in the research phase, this capability will help robots to make split-second decisions or navigate new environments with limited sensor data. This would allow them to quickly understand and adapt to spaces they have never experienced before.The ChatGPT moment for robotics is comingWhile World Labs and GenEx push the boundaries of AI reasoning, Nvidias Cosmos and GR00T are addressing the challenges of equipping humanoid robots with real-world adaptability and interactive capabilities. Cosmos is a family of AI world foundation models that help robots understand physics and spatial relationships, while GR00T (Generalist Robot 00 Technology) allows robots to learn by watching humans like how an apprentice learns from a master. Together, these technologies help robots understand both what to do and how to do it naturally.These innovations reflect a broader push in the robotics industry to equip humanoid robots with both cognitive and physical adaptability. GR00T could enable humanoid robots to help in healthcare by observing and mimicking medical professionals, while GenEx might allow robots to navigate disaster zones by inferring environments from limited visual input. As reported by Investors Business Daily, Nvidia CEO Jensen Huang said: The ChatGPT moment for robotics is coming.Another company working to create physical AI models is Google DeepMind. Timothy Brooks, a research scientist there, posted this month on X about company plans to make large-scale gen models that simulate the physical world.These emerging physical world models will better predict, plan and learn from experience, all fundamental capabilities for future humanoid robots.Google is building world simulation models. Source: X.com https://x.com/_tim_brooks/status/1876327325916447140The robots are comingEarly in 2025, humanoid robots are largely prototypes. In the near term, they will focus on specific tasks, such as manufacturing, logistics and disaster response, where automation provides immediate value. Broader applications like caregiving or retail interactions will come later, as technology matures. However, progress with AI and mechanical engineering is accelerating such humanoid robot development.Consulting firm Accenture recently took note of the developing full stack of robotics hardware, software and AI models purpose-built for creating machine autonomy in the human world. In their 2025 Technology Vision report, the company states: Over the next decade, we will start to see robots casually and commonly interacting with people, reasoning their way through unplanned tasks, and independently taking actions in any kind of environment.A timeline of past and estimated future robot adoption. Source: Accenture Technology Vision 2025 Technology Vision 2025Wall Street firm Morgan Stanley has estimated that the number of U.S. humanoid robots could reach eight million by 2040 and 63 million units by 2050. The company said that, in addition to technological advances, long-term demographic shifts creating labor shortages may help drive the development and their adoption.Building trustworthy robotsBeyond the purely technical obstacles, potential societal objections must be overcome. Without addressing these concerns, public skepticism could hinder the adoption of humanoid robots, even in sectors where they offer clear benefits. To be successful, deployed humanoid robots would need to be seen as trustworthy, and people will need to believe that they help society. As noted by MIT Technology Review, few people would feel warm and comfortable with such a robot if it walked into their living room right now.To address challenges with trust, researchers are exploring how to make robots appear more relatable. For instance, engineers in Japan have created a face mask from human skin cells and attached it to robots. According to a study published last summer and reported by The New York Times, the studys lead researcher said: Human-like faces and expressions improve communication and empathy in human-robot interactions, making robots more effective in health care, service and companionship roles. In other words, human-like appearance will improve trust.In addition to appearing trustworthy, human-like robots will need to consistently behave ethically and responsibly to ensure human acceptance. In public spaces, for example, humanoid robots with cameras might inadvertently collect sensitive data, such as conversations or facial details, raising concerns about surveillance. Policies ensuring transparent data practices will be critical to mitigate these risks.The next decadeIn the near term, humanoid robots will focus on specific tasks, such as manufacturing, logistics and disaster response, where automation provides immediate value. These specialized roles highlight their current strengths in structured environments while broader applications, like healthcare, caregiving and retail operations will emerge as technology matures.As humanoid robots become more visible in daily life, their presence will profoundly impact and potentially reshape human interactions and societal norms. Beyond performing tasks, these machines will integrate into the social fabric, requiring humans to navigate new relationships with technology. Their adoption could ease labor shortages in aging societies and improve efficiency in service sectors, but may also provoke debates about job displacement, privacy and human identity in an increasingly automated world. Preparing for these shifts will demand not just technological progress, but thoughtful societal adaptation.By addressing challenges and leveraging the efficiency and adaptability of humanoid robots, we can ensure these technologies serve as tools for progress. Shaping this future isnt just the responsibility of policymakers and tech leaders it is a conversation for everyone. Public participation will be essential to ensuring humanoid robots enhance society and address real human needs.Gary Grossman is EVP of technology practice at Edelman and global lead of the Edelman AI Center of Excellence.DataDecisionMakersWelcome to the VentureBeat community!DataDecisionMakers is where experts, including the technical people doing data work, can share data-related insights and innovation.If you want to read about cutting-edge ideas and up-to-date information, best practices, and the future of data and data tech, join us at DataDecisionMakers.You might even considercontributing an articleof your own!Read More From DataDecisionMakers
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