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OpenAI
OpenAI is developing a humanoid platform that integrates advanced machine learning algorithms and robotics. This platform utilizes deep reinforcement learning for adaptive behavior and natural language processing for human interaction. The architecture includes sensor fusion for environmental awareness and actuators for precise movement. The system aims to enhance human-robot collaboration in various applications, including industrial automation and service robotics.
RobotToday Initiative
Robotics needs a service framework.
RSF defines a common language for robot service capability, lifecycle operations, certification pathways, and service-provider networks.
WAIC 2026: Embodied Intelligence Enters Industrial Deployment Era
WAIC 2026 in Shanghai (July 17–20) saw 200+ embodied intelligence companies, 300+ live robots, and first confirmed humanoid deployments in logistics and pharmacy. RobotToday engineering analysis.
Google Expands AI Mode to Integrate with Popular Apps Like Instacart and Canva
Google has announced an update to its AI Mode, allowing users to link and interact with select apps such as Instacart, Canva, and YouTube. This enhancement enables users to complete tasks directly within the conversational search experience, moving beyond simple question answering. The integration of these apps is significant as it positions Google to compete more effectively with rivals like OpenAI’s ChatGPT and Anthropic’s Claude, both of which offer app integrations. By encouraging users to utilize AI Mode for planning and shopping, Google aims to increase engagement with its platform. Looking ahead, Google plans to expand the range of supported apps, building on previous capabilities introduced at Google I/O. No further timeline was disclosed at the time of publication.
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Microsoft Trains Sales Team to Critique OpenAI and Anthropic AI Products
Microsoft is reportedly preparing its sales team to adopt a more aggressive stance against competitors in the AI sector, specifically targeting OpenAI and Anthropic. During a recent internal meeting, executives emphasized the importance of highlighting the efficiency and cost-effectiveness of Microsoft's in-house AI models compared to those of rivals like Google and Anthropic. This strategy is significant as it marks a shift in Microsoft's approach towards companies it has historically collaborated with for AI models. The company has been transitioning away from using OpenAI and Anthropic's models in flagship applications like Word and Excel, opting instead for its own solutions as a cost-saving measure. This change reflects a broader competitive strategy aimed at enhancing Microsoft's market position in the AI landscape. Looking ahead, it will be crucial to observe how this new sales strategy impacts Microsoft's relationships with OpenAI and Anthropic, especially following the recent amendment of their partnership agreement. No further timeline was disclosed at the time of publication.
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OpenAI Introduces Codex Micro Keyboard for Enhanced AI Coding Workflows
OpenAI has launched its first hardware product, the Codex Micro, a specialized keyboard designed for software developers. This compact device, developed in collaboration with Work Louder, features dedicated controls that facilitate the management of multiple coding tasks and AI agents, enhancing coding efficiency. The Codex Micro is significant as it represents OpenAI's commitment to AI-assisted software development, an area where the company has made substantial investments. With features like illuminated keys for task status and customizable controls, the keyboard aims to streamline the coding process, allowing developers to focus on their work without excessive reliance on software menus. Looking ahead, the Codex Micro is priced at $230 and will be available through Supply Co. While the exact number of units has not been disclosed, the device's design and functionality suggest a growing trend towards specialized hardware in the AI development space. No further timeline was disclosed at the time of publication.
AI and Robotics
Microsoft CEO Satya Nadella Warns Companies About AI Data Risks and Ownership
In a recent blog post, Microsoft CEO Satya Nadella raised concerns about the risks associated with using AI models from proprietary labs like OpenAI and Anthropic. He highlighted that companies are not only paying for AI usage but are also inadvertently sharing sensitive business information, which could be exploited by these labs as they learn from user interactions. Nadella emphasized that enterprises are effectively teaching AI models about their unique business nuances, which could lead to competitors gaining access to invaluable institutional knowledge. He criticized the current model where AI companies can freely train on public data while imposing restrictions on how enterprises can learn from their models. To address these concerns, Nadella suggested that companies should retain ownership of their data and develop proprietary learning environments on cloud platforms. He advocated for the creation of orchestration layers that allow businesses to switch between different AI models, thus avoiding dependency on a single provider. No further timeline was disclosed at the time of publication.
AI Enterprise Microsoft open source ai Satya Nadella
Microsoft Edge 150 Launches with Google Account Sign-In and OpenAI Unveils GPT-5.6
On July 2, Microsoft released version 150.0.4078.48 of Microsoft Edge for desktop, introducing support for Google account sign-ins on both Windows and macOS. This update allows users to log in using either a Microsoft or Google account, enhancing accessibility for users. IT administrators can manage this feature through a new policy called 'NonMicrosoftAccountSignInEnabled'. The significance of this update lies in its potential to streamline user experience and broaden the browser's appeal. By allowing Google account integration, Microsoft Edge aims to attract users who prefer Google's ecosystem, thereby increasing its market share. Additionally, version 150 will be the last to support macOS 13 Monterey, as future updates will require macOS 12 Ventura or later. On July 9, OpenAI officially launched its new AI model series, GPT-5.6, following a limited preview. This series includes three tiers: Sol, Terra, and Luna, each optimized for different performance and cost metrics. The rollout of GPT-5.6 is expected to enhance capabilities in various applications, including coding and cybersecurity, with pricing structured to appeal to a wide range of users. No further timeline was disclosed at the time of publication.
1X Launches Neo Robotic Hand Featuring 25 Degrees of Freedom and Force Transparency
On July 9, 2026, 1X, a unicorn supported by OpenAI, unveiled the Neo robotic hand designed for humanoid robots. This advanced hand boasts 25 degrees of freedom, enabling it to perform a wide range of human-like tasks, such as delicately picking grapes without crushing them and lifting weights up to 20 pounds. The innovative design incorporates a tendon-driven system that enhances dexterity and responsiveness. The significance of the Neo robotic hand lies in its unique 'Force Transparency' technology, which allows for bidirectional communication between the hand and its environment. Unlike traditional robotic hands that operate with high gear ratios, the Neo hand utilizes a low gear ratio of approximately 5:1 to 15:1, enabling it to provide real-time feedback on applied forces. This design not only enhances the hand's functionality but also improves the training of AI models by providing rich physical interaction data. Looking ahead, while the Neo hand addresses fundamental perception challenges, real-world complexities remain a concern. The hand must operate effectively in various domestic environments, where it may encounter grease, sauces, or dust. Ensuring safety during interactions with children and maintaining functionality in challenging conditions will be critical for the widespread adoption of this technology. No further timeline was disclosed at the time of publication.
Robotic Hands Humanoid Robots AI Tactile Sensors Robotics Technology
OpenAI's Greg Brockman Takes Charge of Product Strategy Amid Leadership Changes
OpenAI has announced that Greg Brockman, co-founder and president, will take over product responsibilities following the resignation of Fidji Simo due to chronic illness. Simo, who had been with the company for about a year, will transition to a part-time advisory role. Brockman will now oversee key initiatives including ChatGPT and enterprise teams, reporting directly to CEO Sam Altman. This leadership change comes as OpenAI prepares for a potential IPO, having confidentially filed its prospectus in June. With a valuation of $852 billion, the company faces pressure to generate revenue amid increasing competition from firms like Anthropic and Google. Notably, ChatGPT's market share has dipped below 50%, prompting OpenAI to promote its AI coding assistant, Codex, to attract more users. Looking ahead, OpenAI's next steps include solidifying its market position and preparing for its IPO, which is expected to occur next year. No further timeline was disclosed at the time of publication. Brockman's leadership will be crucial as the company navigates these challenges and seeks to maintain its competitive edge in the rapidly evolving AI landscape.
OpenAI Launches GPT 5.6 as Preferred Model for Microsoft 365 Copilot Integration
OpenAI has announced that its latest model, GPT 5.6, will serve as the preferred AI model for Microsoft 365 Copilot, enhancing productivity applications like Word, Excel, and PowerPoint. This announcement came amid reports of Microsoft increasingly utilizing its in-house models, known as MAI, to reduce costs. The launch event took place on Thursday, reinforcing the ongoing collaboration between the two companies despite speculation about a potential rift. The significance of this announcement lies in the continued integration of OpenAI's advanced AI capabilities within Microsoft's suite of productivity tools. OpenAI emphasized its commitment to enhancing user experience across Microsoft applications, which could lead to improved functionality and user engagement. The partnership aims to leverage AI to benefit a broader range of individuals and organizations, maintaining a competitive edge in the productivity software market. Looking ahead, it remains to be seen how the relationship between OpenAI and Microsoft will evolve, especially with Microsoft’s in-house models gaining traction. No further timeline was disclosed at the time of publication regarding future developments or enhancements to the partnership. Observers will be keen to monitor how this dynamic affects both companies' strategies in the AI and productivity sectors.
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OpenAI introduces GPT-5.6 models with enhanced efficiency and cybersecurity features
OpenAI has launched its latest family of models, GPT-5.6, featuring three variants: Sol, Terra, and Luna. Announced on Thursday, these models promise significant advancements in enterprise applications, coding, and scientific research. Notably, Sol is reported to be 54% more token efficient for coding tasks, positioning it as a leading option in the AI landscape. The introduction of GPT-5.6 is significant as it aims to enhance cybersecurity capabilities, with OpenAI claiming it is their strongest model yet in this area. The model supports various defensive activities such as threat modeling and code review, addressing concerns raised by previous regulatory scrutiny. This launch is strategically timed to compete with offerings from rivals like Anthropic, with OpenAI asserting that its models outperform competitors in key metrics. Looking ahead, OpenAI's new models are now available across platforms including ChatGPT and Codex, with pricing structured per million tokens. The company has not disclosed specific timelines for future updates or enhancements, but the competitive landscape suggests ongoing developments in AI model capabilities and market positioning.
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AI Models Overthink Problems—and It’s a Security Risk
Large language models (LLMs) that can think through problems step-by-step have significantly increased the scope of tasks that AI can tackle. But new research suggests these reasoning capabilities also introduce a critical vulnerability that could allow attackers to slow these systems to a crawl.While earlier generations of LLMs would immediately produce a response to a user’s request, today’s most advanced models generate an internal monologue where they break down the problem into steps and reason about the best way to tackle it before providing an answer. This has allowed AI to tackle increasingly complex problems, particularly in areas like coding and math.However, previous research has shown that these models are susceptible to sometimes producing excessively long streams of reasoning that do little to boost performance, a phenomenon known as “overthinking.” In research presented this week at the International Conference on Machine Learning 2026 in Seoul, researchers from Zhejiang University and e-commerce giant Alibaba in China demonstrate that they can deliberately induce overthinking by subjecting models to logically inconsistent prompts. The result is a form of denial-of-service attack on commercial AI models.Evolutionary Prompt Attack on LLMsThe team has developed an evolutionary algorithm that corrupts the logical structure of prompts, causing models to spiral into overthinking as they attempt to reason through fundamentally unsolvable problems. Generating longer responses costs more and increases the load on a model provider’s servers, so if done at scale, the researchers say, this could significantly degrade the experience of legitimate users. The attack was effective against reasoning models from leading AI companies including DeepSeek-R1, Alibaba’s Qwen3-Thinking, OpenAI’s GPT-o3, and Google’s Gemini 2.5 Flash and resulted in outputs up to 26 times as long as standard responses on a standard math benchmark.“Across multiple datasets and reasoning models, our method substantially amplifies the output length,” Wei Cao, a masters student at Zhejiang University, wrote in an email to IEEE Spectrum. “Our results suggest that overthinking is not an isolated phenomenon specific to individual models, but rather a shared vulnerability among modern reasoning models.”The team’s approach builds on previous research from another group of researchers that showed reasoning models tend to overthink when faced with a question in which a key premise has been removed—such as asking how far someone who walks ten miles a day covers in total without specifying how many days they walked for. Rather than identifying that the problem is unsolvable, models often engage in extended but ultimately fruitless reasoning loops in an attempt to answer the question.Taking the idea a step further, the authors took 940 problems from three math benchmark datasets and used an LLM to break down their logical structure into a set of premises and a final question. The genetic algorithm then jumbled these up using a variety of “mutations,” including swapping premises between problems, adding extra premises to problems, deleting existing premises from problems, and swapping the final questions between two sets of premises.After each round of mutations, the problems are scored on how many words they cause a target model to output and also whether they increase the frequency of specific linguistic markers of overthinking—words like “but,” “wait,” “maybe,” or “alternatively.” The problems that scored highest on both measures are retained and the remaining ones are jumbled up again, and this process is repeated for five generations. Crucially, the approach doesn’t require access to the internals of a model and can generate malicious prompts by simply querying the target, which makes it possible to attack closed-source commercial services, says Cao.Overthinking Vulnerability in AI ModelsThe researchers found that the approach consistently led to outputs several times longer than those generated by the unmodified questions for the reasoning models they tested it on. The biggest jump came from DeepSeek-R1 on the MATH dataset, which is made up of problems from high school math competitions, where the maximum output was 26.1 times as long as the longest response the model provided to unaltered questions. While the main thrust of the research was focused on math problems, the authors also tested it on coding, scientific reasoning, and dialogue challenges, and observed significant jumps in output length in all three.One challenge for the approach is that developing the malicious prompts requires repeated queries to expensive reasoning models, which Cao admitted could limit its cost-effectiveness. However, the researchers also demonstrated that when they used a smaller, cheaper model to generate the malicious prompts they were still able to induce the target models to produce outputs several times longer than normal. This ability to transfer malicious prompts between models significantly increases the attack’s feasibility, Cao wrote.However, he pointed out that the goal of the research is not to develop a practical DoS attack on reasoning models. Factors like the providers’ pricing model, rate limiting policies, context window size, and existing defenses could all impact how effective the approach is. The intention is instead to highlight these models’ vulnerability to logically inconsistent prompts so that providers can attempt to mitigate the problem.“Our objective is not to demonstrate that large-scale attacks can be launched at negligible cost, but rather to establish that this attack surface exists,” he wrote. “Our results indicate that the vulnerability represents a realistic security concern.”
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ROBOTTODAY Weekly June 30 – July 4, 2026
Unitree wins CSRC approval for China’s first humanoid IPO, Korea unveils ₩312T AI investment, RoboCup 2026 opens in Incheon, and Paris launches Europe’s inaugural Physical AI summit.
The EV Déjà Vu: Why China's Humanoid Robot Blitz May Be Winning the Battle — but Losing the War
China controls 80% of humanoid robot shipments and crushes hardware costs. But is winning the body enough? A deep analysis of the US-China robot war beyond the EV analogy.
Capex Analysis 2025: AI Hyperscalers vs Humanoid Robots — Financing Risk Deep Dive
Compare how Microsoft, Google, Oracle, Tesla Optimus, Figure AI and UBTECH finance their Capex. Supply chain risk, ROIC analysis and a 3-dimension investment framework included.
CONSTRUCTION ROBOTICS | BUSINESS MODELS & INVESTMENT LANDSCAPE
Construction robotics attracted $4.4 billion in built environment tech funding through Q3 2025. SoftBank acquired ABB Robotics for $5.375 billion. RaaS is displacing capex models. AI-native platforms command 39x revenue multiples. This is where money meets machines.
GLOBAL ROBOTICS INDUSTRY Comprehensive Sector Overview
A comprehensive global robotics industry overview for 2025, analyzing 14 key market segments — from industrial and humanoid robots to logistics AMRs, military systems, and service robots — with expert market sizing, US case studies, five-year forecasts, and bilingual English-Chinese analysis for executives and investors.
Meta Acquires ARI to Capture the Brain of the Humanoid Robot
Meta’s acquisition of Assured Robot Intelligence (ARI) signals a pivot from hardware race to intelligence capture. We break down why Meta moved now, what ARI does, and how Amazon, Tesla, NVIDIA and Apple are responding — with different bets and different risks.
TARS AI Closes $455M Pre-A Round, Setting China Embodied-AI Financing Record
TARS AI closes a record $455M Pre-A round led by Hillhouse, Sequoia China and Meituan, setting China’s largest single embodied-AI funding round. Full briefing.
ROBOTTODAY Weekly Industry Briefing March 30 – April 4, 2026
Your weekly robotics briefing: AGIBOT ships its 10,000th humanoid, UBTech reports a 23-fold revenue surge, Baidu robotaxis freeze in Wuhan, Saronic raises $1.75B, and Generalist’s GEN-1 hits 99% task success. March 30 – April 4, 2026.
OpenAI Robotics Lead Caitlin Kalinowski Resigns After Pentagon AI Agreement
Caitlin Kalinowski resigns as robotics lead at OpenAI after the company’s AI cooperation agreement with the U.S. Department of Defense, highlighting tensions over military use of advanced AI systems.
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