Tesla has announced a new upgrade called ‘Ludicrous Speed’ for its dual-motor Model S P85D and upcoming Model X. This upgrade promises to extract even more acceleration from these already impressive vehicles, but how does it work? To understand the basics of Ludicrous Speed, we need to look at the underlying technology that powers Tesla’s electric motors.
Teradyne Robotics, the company behind Universal Robots (UR) and Mobile Industrial Robots (MiR), is set to showcase its latest advancements in physical artificial intelligence (AI) at Automate 2026 in Chicago. The event takes place from June 22-25 at booth #1250, where attendees can witness firsthand how Teradyne Robotics’ solutions are transforming industrial automation. According to Jean-Pierre Hathout, President of the Teradyne Robotics Group, ‘Physical AI is on full display across our robotic solutions at Automate.’ The demos presented by Teradyne Robotics are not only impressive but also deployable in real-world settings, with manufacturers able to purchase the physical AI-enabled applications showcased today through the company’s global ecosystem of system integrators and partners. This marks a significant shift towards automating tasks that have traditionally been difficult or impractical for robots, including those in dynamic and unstructured environments.
The City of London has undergone significant changes to its IT services, adopting the ServiceTeam ITSM solution built on the Microsoft Power Platform. This transformation aims to improve service management processes, automate tasks, and enhance overall efficiency.
In a recent webcast presented by Microsoft and technology partner Provance, the City of London shared details about their journey from using a leading ITSM product to implementing ServiceTeam. The presentation highlighted key features and functionality of ServiceTeam, including codeless configuration, automation of service requests and actions, and self-service portals.
ServiceTeam leverages various components of the Microsoft Power Platform, such as Power Apps, Power Automation, and Power BI, to provide a comprehensive IT service management solution. This integration enables users to streamline processes, track performance, and make data-driven decisions.
The City of London’s experience with ServiceTeam has been marked by improved automation capabilities, enhanced reporting, and better asset management. The organization has seen significant benefits from implementing the Microsoft Power Platform, including increased efficiency and reduced manual effort.
During the webcast, attendees gained a comprehensive understanding of ServiceTeam ITSM & ITAM through a detailed summary of the City of London’s journey to ServiceTeam. This included key considerations and objectives that guided their decision-making process.
Lindon, Utah-based RainFocus has announced two new content supply chain integrations with Adobe: the Experience Manager Sites Connector and the Content Advisor. These additions join the existing integration between RainFocus and Adobe Workfront Fusion, creating a comprehensive platform for event marketing teams to streamline their workflows.
These new integrations are designed specifically for event marketing, creative, and web development teams, aiming to eliminate delays in project creation, approval, and publishing processes. By bridging the gap between event planning and web execution, these integrations enable governance with a single source of truth, ensuring brand consistency across thousands of global touchpoints.
The RainFocus platform utilizes agentic AI to orchestrate customer engagement throughout the customer lifecycle, unifying data from in-person, virtual, and hybrid events in a single platform. This unique approach sets it apart from point solutions that often focus on specific aspects of event management.
One key capability is the integration with Adobe Workfront Fusion, which supports efficient event planning and production processes through automated handoffs and template usage. This increases scalability and operational efficiency for both large-scale events and small, localized events.
Another significant feature is the RainFocus and Adobe Experience Manager Sites Connector, which synchronizes session, speaker, and exhibitor data directly into Adobe Experience Manager Content Fragments. This eliminates manual data transfer or redundant updates, ensuring a seamless and consistent brand experience across event websites.
The integration also enables users to leverage AI-powered semantic search to locate approved assets based on natural language descriptions, not just technical metadata. This streamlines the creation of regional event series by eliminating asset duplication and speeding up the process significantly.
Potential use cases for these integrations include automating event lifecycles, supporting large-scale user conferences, conducting high-frequency field marketing, providing brand governance, and more. For instance, organizations can automate event creation workflows using approved Workfront requests or manage thousands of speaker profiles and session updates across complex web architectures in real-time.
RainFocus’ partnership with Adobe is built on technical interoperability, according to Marius Milcher, VP of Platform Strategy and AI at RainFocus. ‘Our integration provides the architectural foundation to automate the event lifecycle,’ he explains, allowing clients to transition from manual data management to strategic, data-driven decision-making.
The integrations are designed for enterprise marketing organizations — specifically field marketing teams, event marketers, creative or brand managers, and web development teams that require high-volume event execution with strict brand governance. The implementation of either Sites Connector or Content Advisor is relatively simple, requiring a RainFocus connector package to be installed in Adobe Experience Manager and authenticated via OAuth.
Stephen Ratpojanakul, Senior Director at Adobe, highlights the benefits of integrating RainFocus into Adobe’s content supply chain solution: ‘This allows our mutual customers to extend the power of Adobe Experience Manager into their customer conferences, field marketing events, and other face-to-face moments during the customer journey.’
The integrations are part of a broader effort by RainFocus to provide AI tools for business that can help organizations streamline event management processes. By leveraging data analysis tools like those provided by Adobe, businesses can gain valuable insights into customer behavior and preferences.
RainFocus has been recognized as a Leader in the 2026 Gartner Magic Quadrant for Event Marketing and Management Platforms. The company maintains ISO 27001, PCI-DSS, and SOC 2 Type II compliance for all five trust criteria, ensuring that sensitive data is handled securely. With over 10,000 events hosted annually, RainFocus has established itself as a leading platform for event marketing and management.
FAQs on the integrations are available online, covering topics such as how RainFocus syncs with Adobe Experience Manager, the benefits of building an event content supply chain with Adobe, and who these integrations are designed for. The implementation process is also detailed, providing step-by-step instructions for setting up either Sites Connector or Content Advisor.
RainFocus is committed to helping organizations run in-person, virtual, and hybrid event programs of all sizes from one system, with the data and personalization needed to drive measurable business results.
Amazon is testing software that decides where warehouse workers should go, but some managers are pushing back against the technology. The tech giant has been developing labor-management systems using machine learning and AI tools to streamline staffing decisions in its North American fulfillment centers and sort centers. According to internal planning documents, Amazon aims to expand these systems across dozens of facilities, potentially saving hundreds of millions of dollars a year.
San Francisco-based Cytronic has secured a significant seed funding of $13.5 million to develop and expand its robotic fulfillment facilities, aiming to help direct-to-consumer brands streamline their shipping costs, delivery times, and scalability without building their own warehouse infrastructure. The investment was led by Slow Ventures through partner Will Quist, with participation from Geek Ventures, Failup Ventures, Alumni Ventures, Spacecadet, Weekend Fund, Mana Ventures, Rice Capital, Script Capital, and several individual investors including Adam Nash and Gokul Rajaram.
Automate 2026, held in Chicago, showcased the latest advancements in automation and robotics. Among the exhibits were humanoid robots that drew significant attention with their human-like appearance and capabilities. However, a closer look reveals a gap between marketing hype and industrial feasibility.
The humanoid robot market has made tremendous progress in recent years, with improvements in hardware and software. The ‘physical AI’ story is driving innovation in robotics, making it more strategic for industries. Nevertheless, the industry needs to discuss humanoids differently, focusing on their actual capabilities rather than just their appearance.
A robot that performs a routine task in a booth may look impressive but does little to demonstrate its industrial feasibility. A humanoid robot’s ability to perform a choreographed task once is not equivalent to delivering value safely and reliably across shifts. The industry must separate real transformation from theater, evaluating humanoids based on what they can actually do.
The humanoid conversation has a significant gap between vision and reality. On one side lies the promise of general-purpose robots that can move through human-designed environments, handle tools, adapt to changing workflows, and take on tasks traditional automation struggles with. This vision is compelling because industrial environments are filled with difficult-to-automate tasks like material handling, inspection, loading/unloading, machine tending, basic tool use, and irregular manipulation.
On the other side lies reality – industrial operations prioritize uptime, safety, throughput, maintainability, integration, and cost. They require systems that work consistently under various conditions, not just in controlled environments. Many humanoid systems can demonstrate useful capabilities but struggle to prove their reliability under industrial conditions.
The question we need to ask is: ‘Is a humanoid the best automation architecture for this outcome?’ The answer may be yes, but often it will be no. If a wheeled mobile manipulator or other alternative can perform the task faster, with lower risk, at a lower cost, and easier certification, then the humanoid form factor becomes a liability rather than an advantage.
The biggest bottleneck in humanoids is scaling. Many systems can demonstrate a single task but struggle to survive the prototype-to-production valley. If users and integrators must custom-engineer these robotic solutions for each segment of each task, reaching full-scale deployment will be slow.
ARC survey data highlights robot scaling challenges as one of the significant hurdles. Industrial deployment often requires deterministic, certifiable safety systems. However, many required standards for humanoids are still evolving, and certification frameworks are not fully in place.
The feasibility gap will close through reliability engineering, safety validation, application-specific tooling, closer integration with existing industrial systems and workflows, and proof that humanoids can deliver measurable operational value.
Humanoid robots need to prove they can do real work in real environments with real economics. Until then, industrial leaders should stay curious, run focused pilots, demand operational evidence, and resist the temptation to confuse human-like motion with industrial value.
The current wave of humanoids may not be about the future of manufacturing but rather a legacy integration layer. Industrial environments have been engineered around humans for longer than they’ve been designed for robots. When we talk about humanoids fitting naturally into these environments, it’s because the environment was built for them – or more accurately, built for us.
There’s real value in bringing a machine that can adapt to existing infrastructure rather than redesigning the factory for automation. Brownfield integration is one of the hardest problems in industrial automation. Ripping and replacing infrastructure is expensive, disruptive, and often unrealistic.
If the only reason a robot needs to look human is because the environment was designed for humans, then we have to ask: are we optimizing for the right system? In some cases, the better answer may still be to redesign the process, simplify the workflow, or deploy a non-humanoid system that performs the task more efficiently.
A humanoid might be the most flexible way to deal with legacy constraints but doesn’t necessarily make it the optimal long-term solution. Humanoids might find their first big success not because they represent the future of automation but because they are compatible with the past.
Human-like bodies are only one possible embodiment of advanced robotic capability. Any robot can, in principle, gain many of these capabilities. In real industrial use cases, other form factors will often make more sense. Over time, capabilities may converge, but for now, it’s smarter to focus on what a system can do rather than its shape.
The idea that large language models alone are the answer is also being challenged. Physics-driven models matter because industrial systems need to understand the likely consequences of actions in the real world – a much more serious industrial requirement than generating fluent text.
Humanoids will continue attracting attention, but the message should be clear: focus on capability over form factor. The companies that win won’t bet solely on a form factor; they’ll build the full Physical AI stack and deploy whatever robotic systems best execute the work.
Chipmaker Intel Corp. is expanding its partnership with Google Cloud into the realm of agentic artificial intelligence, aiming to automate and accelerate silicon development through the use of Google’s Gemini Enterprise platform.
In a move that marks a significant shift in their collaboration, Intel plans to deploy Gemini across its global workforce, enabling it to streamline workflows across various operations, including corporate, engineering, supply chain, and marketing. This will allow the company to leverage autonomous agents to accelerate chip design lifecycles and boost innovation companywide.
According to Cindy Stoddard, Vice President and Chief Information Officer at Intel, the partnership is part of an ambitious ‘AI-powered transformation’ aimed at enhancing employee productivity and efficiency. Gemini Enterprise will serve as a central hub for employees to build and deploy agents, scaling silicon development with elastic cloud infrastructure.
The collaboration between Intel and Google Cloud has been ongoing for some time, but this marks a new phase in their partnership. The chipmaker is now moving beyond isolated AI pilot projects, making dedicated agentic coding assistance and engineering automation capabilities available to its entire organization.
Intel plans to use Gemini’s advanced reasoning skills to streamline development pipelines and automate complex workflows currently performed manually with customized line-of-business agents trained on Intel’s unique business processes. This will enable the company to optimize its development simulations and developer workloads, automating much of this work in the process.
The partnership also extends to marketing and communications teams, who will be able to generate hyper-targeted content for specific audiences using Gemini. Early pilots have already shown promising results, with agents capable of recommending relevant subject matter experts and generating executive-ready messaging.
Intel’s ambitions go beyond just automating workflows; it wants to rely on Gemini to optimize its development simulations and developer workloads. By doing so, the company should be able to dramatically speed up its chip design processes. To support this effort, Intel will augment its existing on-premises compute capabilities with Google Cloud’s C4 and N4 instances.
The announcement builds upon a longstanding partnership between Google and Intel, which has seen them collaborate on various projects, including AI chip interconnects and 5G networks. In April, Google announced that it would adopt multiple future iterations of Intel Corp.’s Xeon central processing units for its public cloud platform to support AI and general-purpose computing workloads.
Holger Mueller, an analyst with Constellation Research, believes this move is a smart one for Intel, allowing the company to leverage Google Cloud’s infrastructure. However, he notes that some might view it as a ‘barney deal’ lacking substance, given Intel’s Xeon processors power Google Cloud’s C4 and N4 compute instances.
Google Cloud Chief Product and Business Officer Karthik Narain is more optimistic about the partnership’s potential to transform enterprise AI capabilities. He emphasizes that pairing Intel’s engineering expertise with Google Cloud’s agentic AI tools creates an autonomous foundation that will fundamentally accelerate how companies design, operate, and scale for the AI wave.
A new carbon capture project in Finland is turning biogas emissions into reusable CO₂, with automation playing a key role in the plant’s operation. The facility will be built at Auris Energia’s biogas site in Mäntsälä, where Suomen Biovoima Oy is developing the technology.
The Finnish project represents an important step towards capturing and reusing carbon emissions instead of releasing them into the atmosphere. In this approach to circular economy initiatives, the plant will recover CO₂ for applications such as concrete production, where it can be permanently bound within building materials.
Valmet has been chosen to provide the automation system for the new CO₂ liquefaction plant. The company’s DNAe Distributed Control System is designed to automate and monitor plant operations from a remote location.
The automation platform will enable Auris Energia to optimize energy use, raw material efficiency, and minimize manual intervention through automated process controls. Secure data transfer, monitoring, reporting, and performance tracking are all part of the system.
According to Suomen Biovoima’s sales manager Mikko Bengts, ‘Capturing and utilizing CO₂ allows us to turn emissions into a valuable resource while improving overall efficiency.’ The partnership with Valmet enables them to integrate modern automation solutions into their projects and scale these innovations in future endeavors.
The project will be implemented in phases. The primary automation system is set for delivery in November 2026, installation planned for December of that year, and startup anticipated during the first quarter of 2027. However, financial details regarding the contract were not disclosed.
Valmet’s senior sales manager Matti Miinalainen noted that ‘This project showcases how automation can support both environmental sustainability and business performance.’ The company will continue to upgrade the system and offer lifecycle services to maintain optimal plant operation over time.
The CO₂ liquefaction plant in Finland is expected to be the first of its kind, capturing, purifying, and liquefying CO₂ produced during biogas generation for industrial reuse. It sets a precedent for future projects aiming to minimize carbon emissions.
Most modern software development relies on open-source components, which are everywhere in codebases. A recent report from cybersecurity firm Black Duck found that nearly all codebases – 98% – contain some open source code after scanning over 947 of them and analyzing almost 3,000 projects between November last year and October this year. As a result, developers must track these dependencies to keep their apps secure and intact.
The problem is, manually keeping tabs on all those open-source components can be overwhelming. With so many dependencies to manage, it’s easy for errors or security vulnerabilities to slip through the cracks.
Morgan State University has announced the launch of a new Bachelor of Science in Artificial Intelligence degree program, designed to prepare students for the rapidly evolving demands of an AI-driven economy. The undergraduate program is offered by the School of Computer, Mathematical and Natural Sciences at Morgan State University, reflecting the accelerating influence of artificial intelligence across every sector of the global economy.
The introduction of this new degree program marks a significant advancement in Morgan’s academic offerings, aligning with emerging technologies and evolving workforce demands. As advances in artificial intelligence continue to reshape the technology landscape, the University adapted its former Bachelor of Science in Cloud Computing program to place AI at its center, creating a curriculum that prepares students to design, develop, and responsibly deploy intelligent systems across various industries.
The new degree program arrives as employers across virtually every sector seek professionals capable of designing, deploying, and responsibly managing AI technologies. Students enrolled in the program will study AI models and intelligent agents, AI-driven cybersecurity, AI applications in cloud computing, and quantum machine learning, while building strong foundations in programming, mathematics, data science, and computational theory.
The curriculum combines rigorous technical instruction with project-based learning, undergraduate research, and real-world AI applications that prepare graduates for careers in artificial intelligence, machine learning, cybersecurity, robotics, cloud computing, data science, and related fields. Unlike traditional lecture-based instruction, every AI and machine learning course offered by Morgan incorporates hands-on projects developed by the University’s faculty and students.
Students will gain practical experience solving real-world challenges while building competitive portfolios for internships, graduate study, and careers with leading technology organizations. The program also emphasizes the ethical development of AI, addressing issues such as fairness, bias, privacy, transparency, security, and the creation of trustworthy intelligent systems. Students will receive personalized support from faculty mentors, graduate students, and an AI-powered advising platform developed within the Department of Computer Science.
According to Shuangbao Wang, Ph.D., professor and chair of the Department of Computer Science, ‘Artificial intelligence has fundamentally changed the direction of computing.’ Rather than simply updating an existing curriculum, Morgan State University reinvented the entire program to ensure students graduate with the knowledge and experience required to lead in an AI-first world.
The new degree program integrates the strengths of 18 artificial intelligence courses offered by the Department of Computer Science into a cohesive undergraduate curriculum focused exclusively on artificial intelligence and its rapidly expanding applications. The curriculum introduces advanced topics, including reinforcement learning, agentic AI for cyber threat detection and analysis, natural language processing, and quantum machine learning.
The launch of this degree program demonstrates Morgan’s commitment to aligning academic excellence with the technologies and industries shaping tomorrow’s workforce. As Paul B. Tchounwou, Ph.D., dean of the School of Computer, Mathematical and Natural Sciences, noted, ‘As artificial intelligence continues to influence scientific discovery, healthcare, business, government, and virtually every other aspect of society, our students must graduate with the technical expertise, critical thinking skills, and ethical perspective necessary to become innovators, researchers, and leaders in this transformative era.’
Morgan State University’s new Bachelor of Science in Artificial Intelligence degree program is designed to equip graduates with the knowledge and experience required to succeed in an AI-driven economy. The program combines rigorous technical instruction with project-based learning, undergraduate research, and real-world AI applications.
The introduction of both offerings underscores Morgan’s broader commitment to designing academic programs that anticipate workforce trends while responding to the evolving needs of employers and society. As two of the University’s fastest-growing academic units, the School of Computer, Mathematical and Natural Sciences and the Earl G. Graves School of Business and Management continue expanding opportunities that position Morgan graduates to compete — and lead — in the innovation economy.
The new degree program is a significant advancement in Morgan State University’s vision as a leading public urban research institution. With its investments in artificial intelligence accelerating across research, teaching, and infrastructure, the University prepares students for careers that increasingly demand technological fluency, interdisciplinary thinking, and adaptable leadership.
Morgan State University was founded in 1867 and is a Carnegie-classified high research (R2) institution offering more than 150 baccalaureate, master’s degree, doctorate, and certificate programs. As Maryland’s Preeminent Public Urban Research University, Morgan serves a multiethnic and multiracial student body and seeks to ensure that the doors of higher education are opened as wide as possible to as many students as possible.
The introduction of this new degree program is part of Morgan State University’s broader efforts to prepare graduates for careers in an AI-driven economy. With its emphasis on project-based learning, undergraduate research, and ethical AI development, the program prepares students not only to use intelligent technologies but also to create them responsibly.
Hundreds of thousands of travelers flying through New York’s busy airports are getting a better experience thanks to revamped airport websites. These overhauled sites at John F. Kennedy International Airport, LaGuardia Airport, Newark Liberty International Airport, and Stewart International Airport in the Hudson Valley now provide real-time information and more streamlined experiences.
The new airport websites have artificial intelligence assistants built-in that answer questions on everything from security wait times to parking availability. This means travelers can plan their pre-flight meals or shopping trips with customizable lists of airport concessions. They also get info on travel-related topics like airport amenities, making it easier for passengers to find what they need.
The Port Authority rebuilt its four airport websites from scratch to prioritize the user experience. Each site now features enhanced customized designs based on usage analytics that guide travelers through the website with a more intuitive navigation system. This helps users quickly find the info they’re looking for without getting lost in menus and sub-menus.
Each AI assistant embedded in an airport website is tailored to that specific location’s needs, so passengers only see relevant information when visiting their destination airport. This minimizes confusion and reduces ‘information overload’ by presenting essential details upfront. It also cuts down on unnecessary clicks and endless scrolling.
The Port Authority wants air travelers to have a one-stop shop for questions about each airport, mirroring the online search experience that digitally savvy users expect. With these upgrades, passengers can find answers quickly without needing multiple click-throughs or long searches.
According to Port Authority Chairman Kevin O’Toole, ‘a truly useful website and web search shouldn’t require an online scavenger hunt.’ He notes that having virtual assistants integrated into the websites makes it easier for travelers to find information without needing multiple clicks or long searches.
The revamped airport websites are part of a broader effort by the Port Authority to improve air travel experiences in New York. For example, John F. Kennedy International Airport is undergoing a massive $19 billion transformation that includes two new large terminals and a renovated roadway network. This major overhaul will provide smoother operations for travelers.
LaGuardia Airport has also seen significant renovations since 2020, earning multiple national and international awards for its design and functionality. The airport’s recent recognition as the best new airport in the world by UNESCO’s Prix Versailles is proof that passengers are already benefiting from improvements across New York airports.
The upgraded websites now live at jfkairport.com (JFK International), laguardiaairport.com (LaGuardia Airport), newarkairport.com (Newark-Liberty), and swfny.com (Stewart International). Travelers can access the AI-powered assistants on each site for a more efficient travel experience. These upgrades aim to reduce stress and make air travel smoother overall by providing real-time information.
The improved airport websites are just one part of the Port Authority’s efforts to enhance passenger experiences in New York. As renovations happen across multiple airports, travelers can expect to see even more improvements in the future as the region continues to evolve its transportation infrastructure. This includes ongoing work at John F. Kennedy International Airport and LaGuardia Airport.
The new airport websites are designed with passengers like you in mind – people who need accurate info fast without getting bogged down by unnecessary menus or complicated navigation systems. The Port Authority’s upgrades will help reduce the stress of traveling through New York airports, making your journey smoother from start to finish.
Chief financial officers (CFOs) and business leaders are increasingly asking how to get more value from their artificial intelligence (AI) investments. For years, software success was measured by adoption metrics such as seats purchased, users active, and licenses renewed. However, understanding AI’s value demands a more comprehensive measure: the work accomplished.
An AI avatar generator is a tool that takes a written script, a chosen voice, and a digital presenter to render a video of the presenter speaking the script with matched lip movement. This technology falls under the broader category of synthetic media, which also includes AI-generated audio and images. Most avatar platforms build on the same basic pipeline: text-to-speech or voice cloning for audio, a rendering engine for the avatar’s face and body, and a lip-sync model that aligns mouth movement to the generated audio.
The European Union has issued two new rules for Google, forcing the company to open its Android operating system to rivals and share search data. The first rule lets Android phone owners choose third-party AI assistants if they prefer, giving users more options when selecting their digital helpers.
The second rule requires Google to allow rival AI assistants to draw on anonymized search data for their own searches. This move aims to level the playing field in Europe’s search market, where some estimates suggest Google dominates with almost 90% of the share.
Google must open up its Android OS and share search data as per EU rules. Failure to comply could lead to penalties worth up to 10% of a company’s annual global revenue, which would be a significant hit for any business.
The European Union has been pushing to promote competition in tech through regulations like these. By opening Google’s Android OS and requiring data sharing with rivals, the EU is giving third-party developers more opportunities to compete with Google’s offerings.
Google’s dominance of Europe’s search market may soon face some stiff competition. With new rules allowing rival AI assistants access to anonymized search data, users can expect a wider range of options when it comes to their digital helpers.
The European Commission notes that this decision provides guidance on several key aspects of Google’s data sharing offer. The commission sees allowing third-party search engines to draw on anonymized search data as a significant step towards promoting fair competition in the tech industry.
Other big tech companies have also faced regulatory scrutiny from Brussels, reflecting growing concerns about fairness and innovation in tech. Governments worldwide are working together to address these issues through regulations that promote data privacy, security, and competition.
The rules will take effect next year, giving Google time to adjust its business practices and comply with the new regulations. Failure to do so could result in significant penalties for the company, which would likely be a major blow.
Google’s decision marks a significant step towards promoting fair competition in tech. However, it remains unclear how companies like Google will respond to these changes, as they continue to navigate shifting regulatory landscapes and increased scrutiny from governments worldwide.
The European Union is committed to promoting innovation and entrepreneurship through regulations that support the growth of third-party developers. By opening up Android OS and requiring data sharing with rivals, the EU aims to level the playing field in tech and give smaller players a fair chance at success.
Allowing rival AI assistants access to anonymized search data will have significant implications for how users interact with their digital helpers on Android devices. With more options available, users can choose from a wider range of AI assistants that better suit their needs and preferences, giving them greater control over their online experience.
The European Commission has stated its support for this decision, which provides guidance on several key aspects of Google’s data sharing offer. The commission sees allowing third-party search engines to draw on anonymized search data as an important step towards promoting fair competition in the tech industry.
The highly anticipated Tesla Model S Plaid has finally arrived, boasting unprecedented acceleration and speed. The new tri-motor version of the electric car was unveiled at a Fremont, California event, where the first 25 customers received their vehicles. Elon Musk, CEO of Tesla, took to the stage to introduce the Plaid upgrade, emphasizing its exceptional performance capabilities.
The $129,990 price tag for the Plaid upgrade is a significant increase from previous models, with some speculating that it was bumped up by $10,000 just before the event. However, Musk’s enthusiasm for the new model remains unwavering, as he proudly declared: ‘Sustainable cars can be the fastest cars, safest cars, most kick-ass cars in every way.’
The Plaid upgrade boasts some impressive statistics, including a 0 to 60 mph time of just 1.99 seconds and a quarter-mile run in 9.23 seconds at 155 mph trap speed. Additionally, it features a top speed of 200 mph and an estimated range of 390 miles on a single charge.
Musk claimed that the Plaid is the first production car to accelerate from 0 to 60 mph in under two seconds, leaving many in awe of its capabilities. He described the experience as ‘something you have to feel to believe,’ suggesting that even he was surprised by the model’s exceptional performance.
Earlier this week, Musk announced the cancellation of an even more powerful version, known as Plaid+, citing no need for it with the current level of performance from the Plaid. This decision has sparked debate among enthusiasts and critics alike, with some questioning whether Tesla is prioritizing profit over innovation.
The dual-motor, long-range Model S remains available at a starting price of $79,990, offering an impressive 412 miles on a single charge. However, it lacks the acceleration and speed capabilities of its Plaid counterpart, leaving many to wonder if the added cost is worth the benefits.
Inside the new Model S, drivers will find a range of innovative features, including a yoke-shaped steering wheel with no stalks and a 17-inch front touchscreen display. The user interface has also been revamped, providing an intuitive experience for drivers. Additionally, the backseat now boasts its own screen for streaming or playing video games.
Musk described the new interior as ‘something you drive around and it really feels like you’re in 2021.’ He emphasized that Tesla’s goal is to minimize driver input, allowing the car to read their mind and adapt accordingly. However, government officials are keeping a close eye on this new technology, with the National Highway Traffic Safety Administration (NHTSA) requesting information about the steering yoke.
The NHTSA has expressed concerns regarding the safety implications of Tesla’s innovative drive system, which eliminates the need for a gear selector and relies heavily on automation. As such, it remains to be seen whether this new technology will gain widespread acceptance or face significant regulatory hurdles.
Tesla CEO Elon Musk had initially teased the Plaid upgrade at the beginning of the year, sparking anticipation among fans and critics alike. Now that the model has finally arrived, production is expected to ramp up significantly in the coming months, with Musk aiming for several hundred cars per week by next quarter.
The growing presence of emerging technologies, including artificial intelligence (AI), is raising concerns about their environmental footprint. As states and local governments grapple with the tension between economic development and community health, public health practitioners are well-positioned to help navigate this complex issue.
In many regions, policy responses vary widely, often reflecting a trade-off between furthering state-level economic interests and addressing local community health and environmental concerns. States have primarily focused on energy reporting, ratepayer protection, and environmental assessment, while local governments have tended to act more directly on land use, zoning, and permitting issues.
For example, Loudoun County in Virginia has ended by-right zoning for data centers, requiring all new applications to undergo public hearings starting from 2025. Kansas City in Missouri has classified data centers as industrial, necessitating council approval and mandatory impact studies on water and electricity rates beginning in 2026. Marana in Arizona has prohibited potable water use for cooling and required water source disclosure since 2024.
The path forward for public health practitioners involves leveraging their expertise to address the environmental impacts of emerging technologies. The three core functions of public health – policy development, assessment, and assurance – provide a concrete framework for this work.
In terms of policy development, public health experts can advocate for health impact assessments in permitting processes, transparency requirements, and community notification standards. They should also contribute their expertise to state and local rulemaking efforts.
Assessment is another critical function where public health practitioners can make a significant contribution. This involves tracking and analyzing cumulative environmental exposures, such as air quality near diesel generators, water availability in stressed regions, and electricity cost burdens on low-income households. Public health experts should push for systematic, mandatory data collection from operators to inform these assessments.
Finally, assurance is essential for ensuring that emerging technologies are deployed in a way that prioritizes community health. This involves monitoring health outcomes over time in affected communities, holding operators and regulators accountable to environmental standards, and guaranteeing vulnerable populations have meaningful access to decision-making processes.
The most critical recommendation from public health experts is the need for communities to have the information, access, and standing necessary to participate in decisions about AI infrastructure that will impact their health for decades to come. By serving as a valuable partner in shaping the ethical rollout of emerging technologies, public health can play a crucial role in balancing economic development with community well-being.
AI agent loops have become an essential tool in automating tasks, but choosing the right loop can be a daunting task. With four different types of loops available – turn-based, goal-based, time-based, and proactive – it’s crucial to understand what each one offers and how they differ from one another. In this article, we’ll explore the characteristics of each loop type and provide guidance on selecting the most suitable option for your specific needs.
A new analysis of nearly 10,000 real-world EV battery tests has revealed a surprising trend in the performance of Tesla Model 3 batteries. The study found that the same car model holds up very differently depending on which type of battery it was built with, and the cheaper lithium iron phosphate (LFP) version comes out on top.
The analysis, conducted by Carla, a Swedish used-EV retailer, looked at data from over 9,954 battery tests conducted in Sweden between 2022 and 2026. The tests were done using AVILOO’s battery diagnostics, which measure the actual state of health rather than relying on the car’s dashboard estimate.
When broken down by battery type, the results showed a striking difference in performance. The LFP pack held its charge better than any nickel-based version of the same car, with an average battery health of 93.3% among cars that had driven more than 62,000 miles. This is a significant gap between the best and worst versions of the same car.
The data also revealed that the two nickel-cobalt-aluminum (NCA) packs from Panasonic, which Tesla previously considered its premium option, degraded the most over time. This counterintuitive result challenges the common assumption that more expensive batteries are inherently more durable.
LFP batteries have long been thought to be less durable than their more expensive counterparts due to their lower energy density and higher cost per kWh. However, this study provides a direct apples-to-apples comparison between LFP and nickel-based cells in the same car model.
The key difference between LFP and nickel-based batteries lies in their chemistry. LFP batteries are cheaper and heavier than their nickel-based counterparts but offer better thermal stability and can tolerate full 100% charging without degrading as quickly. This means that owners of Tesla Model 3s with LFP packs may benefit from improved longevity over time.
The finding aligns with previous studies, including a Tesla-funded study and multiple independent teardowns, which have consistently shown that LFP chemistry ages more gradually than nickel-based cells under high mileage conditions. It also suggests that Tesla’s decision to shift its Standard Range Model 3 and Model Y to LFP packs was not just about cost savings but may have provided an added benefit in terms of battery longevity.
The study is part of a broader analysis of the performance of various EV models, with over 20 vehicles included. The Kia e-Niro and Hyundai Kona mechanical twins topped the ranking at over 97% average battery health among cars past 62,000 miles. Every model in the top 20 averaged above 91%, indicating that many modern EVs are capable of retaining a significant portion of their original capacity even after extensive use.
The results also track with other datasets, including Geotab’s telematics study, which found average annual degradation had improved to about 1.8% per year. This suggests that EV batteries may be more durable than previously thought and could potentially last for over two decades or more under normal driving conditions.
A previously unreported Internet-of-Things (IoT) botnet framework, dubbed TuxBot v3 Evolution, has been discovered by cybersecurity researchers. The framework shows signs of being developed with assistance from a large language model (LLM), although the results are not entirely successful.
The LLM was used to generate botnet code, but it included a safety disclaimer that the developer failed to remove before shipping. This suggests that while the AI did aid in constructing the botnet, several functions in the analyzed samples failed to work correctly. A manual code review would have likely resolved these errors, and it’s possible that more polished iterations of the malware exist out there in the wild.
The TuxBot v3 Evolution framework consists of multiple components, including a C-based bot agent that cross-compiles for various architectures (ARM, MIPS, MIPSEL, MIPS64, x86_64, PowerPC, and RISC-V). The Go-based command-and-control (C2) server features a DDoS-for-hire panel, while the custom exploit virtual machine is designed to target vulnerabilities in IoT devices. Additionally, there’s an automated build system and Docker-based test infrastructure.
The bot agent is responsible for brute-force Telnet access on targeted devices using 1,496 credential pairs. It also incorporates exploit code targeting over 30 IoT device families using known vulnerabilities. The C2 server communicates with the bot agent over an encrypted TCP channel, employing a SHA512 domain generation algorithm (DGA) and peer-to-peer gossip protocol with Ed25519-signed commands.
The framework’s modular design allows for flexibility in its operations. It can resort to various fallback mechanisms, including Internet Relay Chat (IRC), DNS TXT queries, and HTTP polling. The lineage of TuxBot v3 Evolution has been traced back to three different botnets: Mirai, AISURU, and Wuhan. Some functions have also been ported from the open-source MHDDoS Python DDoS toolkit.
At least one sample of the malware was uploaded to VirusTotal on January 20, indicating it’s been around for over six months. Evidence suggests that work on the botnet began a year prior, when the author cloned the MHDDoS repository from GitHub. The framework’s description claims it features a professional-grade C2 platform with multi-user admin panel and automated deployment.
The Go-based C2 server component uses three different TCP ports for incoming connections: 1999 (or 31337), 2222, and 9999. These ports handle encrypted command dispatch to connected bots, interactive shell access over SSH, and programmatic interface via JSON, respectively. Once launched, the botnet follows a pre-defined initialization sequence.
This sequence includes loading the C2 address from a multi-tiered architecture with one primary channel and five alternate mechanisms. It also sets up anti-debugging and anti-VM protections to evade analysis tools. The process name is hidden, persistence is installed, and various sub-modules are launched to mount DDoS attacks and establish communication channels over IRC, HTTP, DNS, and P2P.
The dedicated HTTP scanner can manage up to 128 concurrent connections at any given point in time, operating with the goal of discovering vulnerable web interfaces. Persistence is accomplished through systemd service, cron entries, and a watchdog keepalive process to ensure TuxBot remains operational on compromised machines.
Multiple files contain raw LLM chain-of-thought reasoning left verbatim in comments. These comments reveal the internal reasoning as it worked through porting tasks, complete with self-interruptions, decisions, and references to ‘the user’ (meaning the developer who prompted the LLM). This suggests that the AI was used as a judge of sorts, providing guidance on how to develop the botnet.
The core working functions in TuxBot v3 Evolution, coupled with its reliance on AI tools for businesses, signal accelerated integration of features. The framework’s modular design enables what appears to be single developer to come up with a multi-pronged toolset featuring multiple C2 channels and custom exploit VM.
Shared infrastructure with Kaitori v3.9 and AISURU tooling places the TuxBot operator within the Keksec ecosystem, known for running multiple IoT botnet variants in parallel. This variant aims to go beyond Mirai forks by incorporating encrypted C2, DGA, and a modular exploit system.
The disclosure follows recent emergence of two other botnets: RustDuck and AryStinger. These have targeted routers, IP cameras, Android boxes, and poorly secured servers for co-opting them into networks designed to render online services offline and conduct reconnaissance.