If you had to name 2023’s single-most impactful and disruptive technology, you’d need just two letters: AI. With the release of OpenAI’s ChatGPT in November 2022, we watched a tsunami of AI news and noise throughout the year. And there’s no sign of things slowing down. Even for technology insiders, the rapid pace of generative AI’s development and adoption across all business sectors was simply astonishing. Many organizations that considered themselves to be forward-thinking in 2022 suddenly found themselves playing catch-up in 2023. But if FOMO was a thing last year, this year we say NOMO, as in no more fear of missing out. Instead, look before you leap. As we move forward into a new year, it’s crucial that we commit to a resolution that will help us create significant value for our shareholders, both now and in the years to come. Let’s promise ourselves that this will be the year that we adopt a pragmatic approach to harnessing the vast potential of AI. To do so, we need to first ask ourselves three key questions: Question #1: How will we use AI to meet our specific business objectives? In this new year, the speed and scale of AI implementation will make the progress made in 2023 look stagnant. By 2025, IDC expects Global 2000 companies to devote more than 40% of their core IT budgets to AI-related activities, with worldwide AI spending predicted to exceed $500 billion by 2027. The question, then, is not whether you will shift toward more AI-influenced operations in 2024 but how — and, more importantly, why. AI promises seemingly limitless possibilities for tech-savvy organizations — everything from sorting and analyzing vast amounts of data to improving customer service and patient care. Looking forward, it’s easy to imagine how AI could alleviate supply chain headaches and even create virtual reality training simulations. Whatever their outward manifestation, though, effective AI activities tend to focus on two underlying objectives: expanding capabilities and eliminating waste. In other words, AI is most often used to increase what one can do and improve how it’s done to free up human and financial resources so that you can deploy them more strategically elsewhere in the organization. As IT leaders start thinking about how to incorporate AI into their organizations, they’ll likely focus on generative AI and other advanced AI capabilities to cut down on costs, especially when it comes to mundane tasks and resource optimization. However, while cost-saving is an important consideration, it shouldn’t be the only one on the board. Organizations without a clear vision of what they want to accomplish in 2024 will find plenty of AI bells and whistles but very little direction. AI is a tool, not a mission statement. Focusing on the general use of AI in your organization is not the same as being strategic in how it’s used. In the same way, it’s no different than what we’ve encountered in the past with other transformative technologies, such as cloud computing. As the number of AI features continues to multiply over the next 12 months, it’s crucial that organizations take precautions now to avoid shiny object syndrome, where the potential of adopting this exciting new technology turns from distraction to detriment. To preserve the integrity of their organizations, leaders must evaluate the strategies they use to prioritize investments so that they can optimize spending in preferred technology areas to reach their business goals. Question #2: How will we make sure that we use AI responsibly? While AI can be a powerful tool for achieving business objectives, it can also be a disastrous liability fraught with risks, another reason why organizations should take a deliberate and pragmatic approach to AI adoption. Many people are concerned about the growth of AI. And, as many organizations discovered in 2023, any perceived misuse of AI will significantly harm brand image, regardless of the initial intention. In the public eye, there is no room for error when it comes to AI use. It’s imperative that you and your business stakeholders carefully and regularly review procedures to ensure the ethical use of AI tools and AI-generated outputs. Even if your organization is not presently active in Europe, the EU’s forthcoming Artificial Intelligence Act should inform your AI-related policy decisions. And with a recent hearing on the oversight of AI in the United States Senate, it’s possible the American government will issue guidance as well. At the very least, you should have clear and detailed safeguards in place to address how your organization plans to handle the following issues: Protecting the privacy of customer data Ensuring that proprietary information is not fed into generative AI models Ensuring that AI models and outputs do not reflect bias or prejudice Maintaining vigilant supervision over all AI-related activities Maintaining clear reporting structures for all employees who use generative AI Demonstrating transparency of AI usage to stakeholders inside and outside of the organization As you might expect, your legal department should be deeply involved in these conversations. Question #3: How will we make sure our employees use AI successfully? Ultimately, AI adoption is not just an IT issue: it is a workforce issue. Are your employees ready? If we’re being honest with ourselves, the answer is probably “not yet.” With any new technology, many companies operate within the “we bought it, so you have to use it” paradigm. This inevitably leads to poor morale and haphazard implementation, which undermine the organization’s goals. ROI quickly becomes DOA. Organizational change often draws out strong emotions from employees. This is especially true when dealing with powerful and disruptive technologies like generative AI. Having conversations with your workforce about AI-related activities before you implement them will go a long way toward calming their fears and making sure you can meet your objectives. Employees need to know: The vision and goals behind your organization’s adoption of AI How AI will augment and enhance the work they do The steps you’re taking to protect them and your customers from AI misuse The steps they should take to report any concerns about specific AI activities How you’ll provide ongoing

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More With 90% of cybersecurity and risk leaders predicting they’ll see budget increases in 2025, many are facing a new era of accountability, with boards wanting to see solid returns on cybersecurity investments. That’s an elusive expectation to deliver on, given that 35.9% of a typical CISO’s budget is going for software. Knowing if, how, when and under what conditions a given cybersecurity software investment delivers a hard-number-based ROI is not easy to do, and such numbers of hard to prove. Clear budget wins do exist, though. They start with automating security operations center (SOC) workflows that are overwhelming analysts with too many conflicting alerts. Automating an endpoint detection and response system is one good place to start, with the goal of reducing alert fatigue in SOCs so analysts can focus on more complex threats and intrusion attempts. Another is automating patch management. CISOs need to move beyond trying to get this done manually with overextended teams, and automate it using the latest AI- and ML-based platforms purpose-built for optimizing patch management network-wide. Forrester’s “Budget Planning Guide 2025: Security and Risk” provides insights into why CISOs are seeing their budgets preserved when other areas of an organization are experiencing layoffs, budget cuts, and, in some cases, new programs being put on hold or canceled altogether. (Note, however, that cybersecurity budgets are, on average, just 5.7% of IT annual spending.) Gartner’s latest forecast update (4Q 2024) of end-user spending for information security reflects the resilience of CISOs’ budgets in the aggregate. These budgets are predicted to grow from $184 billion in 2024 to $294 billion in 2028, and Gartner forecasts the market will grow at a 12.43% compound annual growth rate (CAGR) in four years. Security software is expected to be the fastest-growing segment, consistent with Forrester’s recent findings of CISO spending benchmarks. Gartner predicts spending on security software will grow from $59.9 billion in 2022 to $134.3 billion in 2028, attaining a CAGR of 14.4%. The 10 fastest-growing market segments are outperforming the aggregate market by a slim margin of 12.63%, with cloud security the fastest-growing segment, projected to attain a CAGR of 25.87% from 2024 to 2028.   2025 is shaping up to be the year of CISO fiscal accountability Stephanie Balaouras, Forrester vice president, group director, stated in a recent webinar, “When you think about AI, when you think about some of the novel threats that we’re looking at, when you think about post-quantum encryption, [and] the concerns about that, we are at this inflection point.” Gartner predicts that by 2028, 22% of cyberattacks and data leaks will involve generative AI. Boards aren’t stopping there. While they’re funding the realities of this inflection point by approving security budgets and, in some cases, increasing them, they’re most focused on cutting tech stack sprawl and the expensive licensing fees needed to keep the tech running. Boards’ approval of budgets to improve compliance, reduce AI risks, and reduce tech stack sprawl all hinge on CISOs and their teams delivering this year. Reading between the lines of Forrester’s budget report, we can see that CISOs have entered a new era of accountability. How CISOs are optimizing cybersecurity spending to make the most impact Cloud infrastructure, data, and software are where CISOs are prioritizing their budgets going into 2025, with data-related investments anticipated to make the most significant impact. Forrester sees the increasing adoption of AI and generative AI (gen AI) as driving the needed updates to infrastructure. “Any Gen AI project that we discussed with customers ultimately becomes a data integration project,” says Pascal Matska, vice president and research director at Forrester. “You have to invest into specific capabilities and platforms that run specific AI workloads in the most suitable infrastructure at the right price point, and also drive investments into cloud-native technologies such as Kubernetes and containers and modern data platforms that really are there to help you drive out some of the frictions that exist within the different business silos,” Matska continued. Security and risk leaders are anticipating the most significant changes in their budget next year to be in cloud security, investing in new security technology to run on-premises, and security awareness and training initiatives. Each of those areas is projected to see an increase of 10% or more in 2025 budgets. Protecting revenue is core to CISO accountability One of the most valuable takeaways from Forrester’s cybersecurity planning guide is how essential it is for CISOs to take responsibility for protecting revenue if they want to stand a chance of implementing the guide’s recommendations. VentureBeat continues to see that successful CISOs know how to lead their teams to support and protect revenue, and are often included in board-level discussions and report to the CEO. CISOs who drive gains in revenue advance their careers. “When something touches as much revenue as cybersecurity does, it is a core competency. And you can’t argue that it isn’t,” Jeff Pollard, VP and principal analyst at Forrester, said during his keynote titled “Cybersecurity Drives Revenue: How to Win Every Budget Battle” at the company’s Security and Risk Forum in 2022. Budgeting to protect revenue needs to start with the weakest, most at-risk areas. These include software supply chain security, API security, human risk management, and IoT/OT threat detection. Software supply chains are under siege, with 91% of enterprises falling victim to security incidents in just a year, underscoring the need for better safeguards for continuous integration/continuous deployment (CI/CD) pipelines. Open-source libraries, third-party development tools, and legacy APIs created years ago are just a few threat vectors that make software supply chains and APIs more vulnerable. Persistent attacks on open-source components with wide distribution, including the Log4j vulnerability, are fueling more significant investment in software supply chain security. Where CISOs plan to invest in new technologies Forrester advises CISOs to consider investing in four new technology areas, briefly described below:   Exposure management and cyber

A social CRM solution helps a business to more effectively deploy its marketing and sales strategies across multiple social channels. While social media CRM software can streamline social efforts for a better brand experience, the additional cost may not be worth it, especially if a clear social strategy isn’t already in place. However, for businesses ready to grow their social CRM efforts, top tools like HubSpot, Zoho CRM, and Bitrix24 are a good place to start. 1 monday CRM Employees per Company Size Micro (0-49), Small (50-249), Medium (250-999), Large (1,000-4,999), Enterprise (5,000+) Any Company Size Any Company Size Features Calendar, Collaboration Tools, Contact Management, and more 2 Pipedrive CRM Employees per Company Size Micro (0-49), Small (50-249), Medium (250-999), Large (1,000-4,999), Enterprise (5,000+) Any Company Size Any Company Size Features Calendar, Collaboration Tools, Contact Management, and more 3 HubSpot CRM Employees per Company Size Micro (0-49), Small (50-249), Medium (250-999), Large (1,000-4,999), Enterprise (5,000+) Micro (0-49 Employees), Small (50-249 Employees), Medium (250-999 Employees), Large (1,000-4,999 Employees) Micro, Small, Medium, Large What is social CRM? Social CRM is customer relationship management software that offers advanced social selling functionality through social media marketing and integrations. This is especially key for businesses looking to capture more leads through social channels and improve their brand awareness. Like many SaaS tools, a social CRM solution is designed to force multiply your efforts by applying digital conveniences, such as: Automation: Automating simple, repetitive tasks. Bulk processing: Facilitating batch processing of tasks that are performed in bulk. Streamlined access: Consolidating interfaces and controls, bringing all of the necessary functions into a single dashboard. Data transparency: Aggregating information into a single record and improving data integrity. Top social CRM tools Obviously, each provider will have different approaches and intended use cases. However, most will generally be built to provide certain core features and functions. Single source of truth While a standard CRM solution will do a good job of tracking contact details for leads as they travel down the sales funnel, convert into customer accounts, and switch to retention mode, that’s pretty much where it ends. With a social CRM, it’s possible to connect lead and customer profiles to their social profiles. That way, sales reps can more easily track their interactions with the company’s brand. This allows customers to start the discussion where they like, and sales reps can migrate it to another platform if they see fit. Consistency in brand experience Social CRM software makes it easier to deliver the same experience across your whole digital footprint. Brand identity and brand experience are important, and it’s easier to achieve positive interactions when they are consistent from one domain to another. Just as customers and leads don’t want to repeat themselves just because they switched from one social channel to another, they also don’t want to feel like there are major shifts in how interactions are handled. If they can get a response in minutes on one platform, they expect it to be just as quick on others. This experience is more difficult to provide when manually monitoring and responding to discussions on social media. It’s much easier when everything can be done from a single suite of tools. Integrated controls A social CRM solution can function as a “master key” of sorts, allowing sales and marketing reps to create and schedule posts for multiple channels, monitor incoming messages and tags, track performance and metrics, and more. This saves significant time and overhead by putting all the necessary interfaces and controls in one place. It reduces the hassle of logging into and accessing multiple social accounts, sharing passwords, and posting on multiple platforms or profiles. Automated reconnaissance Social CRM solutions can reduce the grind of managing social media accounts and engagement. You can set up alerts that monitor for mentions and tags and then notify you when something pops up. You can perform more advanced searches the same way. You can more effectively research and observe what works and create engagement amongst your target audience. You can also track trends in more or less real-time, leading to better response times when a new opportunity presents itself. Enhanced awareness Social CRM tools help alleviate the amount of effort required to keep up with rapidly-evolving conversations. By automating the monitoring and searching and putting all of the notifications in the same place, these solutions can cut down on the effort required to keep a finger on the pulse of whatever you need to do. Faster response times mean you’ll be more effective at putting out fires or fanning the flames. Analytics insights The right social CRM tool can report on the numbers, providing insight into social media performance to help you plan for more effective strategies and identify problem areas. The key here is that you can collect analytics data from across disparate platforms — data that’s normally siloed and difficult to extract, transform, and load into a cohesive database — to say nothing of turning into a report that makes any sense. Benefits of social CRM Setting aside any solution-specific details, most pros and cons for social CRM are the same whether you’re talking about strategy or software. So, let’s take a look at whether the benefits of social CRM would outweigh the challenges. Streamlined social efforts Consolidated controls mean fewer dashboards to juggle, less to manage, and easier implementation of efforts across social channels. Improved brand experience and customer service Businesses of any size, including startups, can deliver better brand experience and customer service through increased consistency, improved response time, and minimized wasted and redundant efforts. Increased trust and brand loyalty By exposing yourself to the risk of public discourse in third-party spaces, you demonstrate a willingness to deliver on promises—even when inconvenient or costly. Social CRM: Benefits and drawbacks comparison Benefits of social CRM Challenges of social CRM Streamlined social efforts. Improved brand experience. Faster customer service. Increased trust and brand loyalty. Social platforms are “shared” spaces. Risks of “court of public opinion.” Social

While it’s possible to send a fax using Voice over Internet Protocol (VoIP), it’s not a good idea. VoIP fax is not reliable, at all, and there is no IT person in the world who would recommend that you send a fax with VoIP. Faxing is built on analog technology that isn’t compatible with digital VoIP phone systems that make calls over the internet. I’ll explain exactly why that is and share specific problems you may run into when attempting to send VoIP faxes. If you need to send a fax without a fax machine or landline, there are simple online fax services that work far better than trying to use VoIP to send a fax. Okay — that’s the quick rundown of key information. Let’s dig into the details. 1 RingCentral RingEx Employees per Company Size Micro (0-49), Small (50-249), Medium (250-999), Large (1,000-4,999), Enterprise (5,000+) Medium (250-999 Employees), Large (1,000-4,999 Employees), Enterprise (5,000+ Employees) Medium, Large, Enterprise Features Hosted PBX, Managed PBX, Remote User Ability, and more 2 Talkroute Employees per Company Size Micro (0-49), Small (50-249), Medium (250-999), Large (1,000-4,999), Enterprise (5,000+) Any Company Size Any Company Size Features Call Management/Monitoring, Call Routing, Mobile Capabilities, and more 3 CloudTalk Employees per Company Size Micro (0-49), Small (50-249), Medium (250-999), Large (1,000-4,999), Enterprise (5,000+) Any Company Size Any Company Size Features 24/7 Customer Support, Call Management/Monitoring, Contact Center, and more Why VoIP fax struggles When you make a VoIP phone call, the sound of your voice is broken down and converted into smaller digital packets that travel over the internet. Each packet contains information that identifies it within the full series of signals. Even if it arrives out of order, each piece can be reassembled into its complete original message on the other end. Fax machines are made to send and receive the analog tones of the public switched telephone network rather than the digital packets associated with VoIP. Unlike voice calls, fax data is highly timing-sensitive and doesn’t tolerate packet loss, jitter, or delays. Essentially, the two technologies rely on different languages — you can’t just hook an analog device (fax machine) to a digital network (the internet) and expect them to communicate flawlessly. Connecting an analog fax machine to a digital network requires specialized solutions, such as a fax-specific protocol like T.38. However, this depends on both the VoIP provider and the receiving device supporting the protocol to ensure compatibility. SEE: Learn more about the differences between landline and VoIP communication. What are the issues with VoIP fax? VoIP technology was designed to digitize and transmit voice signals, not fax tones. Fax machines rely on analog tones that VoIP networks struggle to handle reliably. This creates several challenges when sending faxes over VoIP. 1. Packet loss and jitter When a fax machine’s tones are digitized and transmitted over a VoIP network, the data is broken into packets. These packets can experience delays, arrive out of order, or be lost entirely during transmission. Such issues, known as jitter and packet loss, make it difficult for the receiving fax machine to reassemble the data correctly. SEE: Discover how to fix network jitter for good. 2. Bandwidth limitations Fax transmissions require more bandwidth than voice calls due to the amount of data involved. During periods of heavy network use, insufficient bandwidth can lead to failed transmissions. SEE: Learn how to optimize your network for VoIP, fax, and other business communications. 3. Protocol interoperability Fax machines must use the same protocol — typically T.30 or T.38 — to communicate effectively. If the sending and receiving devices are not aligned, errors occur, and the transmission can fail. The newer G.711 codec addresses some compatibility issues but still relies on both machines supporting it. SEE: Learn more about using the right VoIP codecs. 4. Network firewalls Firewalls and NAT (Network Address Translation) filtering can block or disrupt VoIP fax transmissions by stripping necessary data from the packets. Disabling features like SIP ALG can help but may expose your network to security risks. SEE: Check out the different types of Network Address Translation and when to use each one. VoIP fax alternatives Use an online fax service When you send a fax using an online service, the platform processes it through their backend infrastructure, converting it into a format suitable for the recipient’s device — whether it’s an email, a web portal, or a physical fax machine. This ensures the reliability and compatibility of a traditional fax while eliminating the need for additional hardware on your end. The best online fax services have interfaces that are highly user-friendly, accessible via web browsers or mobile apps. While internet access is required to initiate the fax, recipients using traditional fax machines do not need internet access. If you only need to send an occasional fax, free or pay-per-use online fax services might suit your needs. If you need to fax a check or another sensitive document, just remember that fax is only as secure as its network. Using reputable providers is always a good idea. For businesses, subscription plans offer enhanced features, such as secure document storage, integrations with productivity tools, and support for higher volumes. Use a fax ATA A fax ATA (Analog Telephone Adapter) is a device that connects the fax machine to a modem or router, converting analog signals into digital data for transmission over a VoIP network. This is a practical solution for those who want to move communication to digital channels while continuing to use existing equipment. The key to success with this setup is choosing a VoIP provider that explicitly supports fax services as not all do. With the right provider, a fax ATA can deliver reliable performance without requiring a transition to online fax services. For businesses that already have functioning fax machines and prefer to avoid additional expenses or workflow changes, a fax ATA is an effective and straightforward option. SEE: Check out our RingCentral review to learn more about our favorite fax-enabled VoIP service.  Maintain separate

Responsibility in action So, what can we do? First, we must recognize that AI doesn’t develop in a vacuum. It’s shaped by people, policies, and cultural norms. To ensure it grows responsibly, we need diverse voices at the table — developers, policymakers, and community leaders who can represent the needs of all users, not just the privileged few. Second, we need stronger governance frameworks that emphasize transparency, fairness, and accountability. This includes mandating bias testing, diversifying datasets, and holding companies accountable for the societal impacts of their technologies. Finally, we need a cultural shift. AI should be seen not just as a technological achievement, but as a societal one. Its development must prioritize equity, inclusion, and responsibility. By doing so, we can harness AI’s potential to bridge gaps and create opportunities, rather than perpetuate harm. source

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Nvidia has launched its Cosmos world foundation model platform to accelerate physical AI development. In a keynote speech at CES 2025 by Nvidia CEO Jensen Huang, the company said the platform includes state-of-the-art generative world foundation models, advanced tokenizers, guardrails and an accelerated video processing pipeline built to advance the development of physical AI systems such as autonomous vehicles (AVs) and robots. Physical AI models are costly to develop, and require vast amounts of real-world data and testing. Cosmos world foundation models, or WFMs, offer developers an easy way to generate massive amounts of photoreal, physics-based synthetic data to train and evaluate their existing models. Developers can also build custom models by fine-tuning Cosmos WFMs. Cosmos models will be available under an open model license to accelerate the work of the robotics and AV community. Developers can preview the first models on the Nvidia API catalog, or download the family of models and fine-tuning framework from the Nvidia NGCTM catalog or Hugging Face. “It is trained on 20 million hours of video,” Huang said. “Nvidia Cosmos. It’s about teaching the AI to understand the physical world.” Cosmos generates synthetic data Leading robotics and automotive companies, including 1X, Agile Robots, Agility, Figure AI, Foretellix, Fourier, Galbot, Hillbot, IntBot, Neura Robotics, Skild AI, Virtual Incision, Waabi, and XPENG, along with ridesharing giant Uber are among the first to adopt Cosmos. “The ChatGPT moment for robotics is coming. Like large language models, world foundation models are fundamental to advancing robot and AV development, yet not alldevelopers have the expertise and resources to train their own,” said Jensen Huang, founder and CEO of Nvidia, in a statement. “We created Cosmos to democratize physical AI and put general robotics in reach of every developer.” Nvidia’s journey to CES 2025 Open world foundation models to accelerate the next wave of AI Nvidia Cosmos’ suite of open models means developers can customize the WFMs with datasets, such as video recordings of AV trips or robots navigating a warehouse, according to the needs of their target application. Cosmos WFMs are purpose-built for physical AI research and development, and can generate physics-based videos from a combination of inputs, like text, image and video, as well as robot sensor or motion data. The models are built for physically based interactions, object permanence, and high-quality generation of simulated industrial environments — like warehouses or factories — and of driving environments, including various road conditions. In his opening keynote at CES, Huang showcased ways physical AI developers can use Cosmos models, including for: Video search and understanding, enabling developers to easily find specific training scenarios, like snowy road conditions or warehouse congestion, from video data. Controllable 3D-to-real synthetic data generation, using Cosmos models to generate photoreal videos from controlled 3D scenarios developed in the Nvidia Omniverse platform. Physical AI model development and evaluation, whether building a custom model on the foundation models, improving the models using Cosmos for reinforcement learning or testing how they perform given a specific simulated scenario. Foresight — the ability to predict the results of a physical AI model’s next potential actions — to help it select the best action to follow. Multiverse simulation, using Cosmos and Omniverse to generate every possible future outcome an AI model could take to help it select the best and most accurate path. Nvidia is marrying tech for AI in the physical world with digital twins. Building physical AI models requires petabytes of video data and tens of thousands of compute hours to process, curate and label that data. To help save enormous costs in data curation, training and model customization, Cosmos features: An Nvidia AI and CUDA-accelerated data processing pipeline, powered by Nvidia NeMo Curator, that enables developers to process, curate and label 20 million hours of videos in 14 days using the Nvidia Blackwell platform, instead of 3.4 years using a CPU-only pipeline. Nvidia Cosmos Tokenizer, a state-of-the-art visual tokenizer for converting images and videos into tokens. It delivers eight times more total compression and 12 times faster processing than today’s leading tokenizers. The Nvidia NeMo framework for highly efficient model training, customization and optimization. World’s largest physical AI industries adopt cosmos Pioneers across the physical AI industry are already adopting Cosmos technologies. 1X, an AI and humanoid robot company, launched the 1X World Model Challenge dataset using Cosmos Tokenizer. XPENG will use Cosmos to accelerate the development of its humanoid robot. And Hillbot and SkildAI are using Cosmos to fast-track the development of their general-purpose robot. “Data-scarcity and variability are key challenges to successful learning in robot environments,” said Pras Velagapudi, chief technology officer at Agility, in a statement. “Cosmos’ text-, image- and video-to-world capabilities allow us to generate and augment photorealistic scenarios in a variety of tasks that we can use to train models without needing as much expensive, real-world data capture.” Transportation leaders are also using Cosmos to build physical AI for AVs. Waabi, a company pioneering generative AI for the physical world, will use Cosmos for the search and curation of video data for AV software development and simulation. Wayve, which is developing AI foundation models for autonomous driving, is evaluating Cosmos as a tool to search for edge and corner case driving scenarios used for safety and validation. AV toolchain provider Foretellix will use Cosmos, alongside Nvidia Omniverse Sensor RTX APIs, to evaluate and generate high-fidelity testing scenarios and training data at scale. Uber is partnering with Nvidia to accelerate autonomous mobility. Rich driving datasets from Uber, combined with the features of the Cosmos platform and Nvidia DGX Cloud, will help AV partners build stronger AI models even more efficiently. “Generative AI will power the future of mobility, requiring both rich data and very powerful compute,” said Dara Khosrowshahi, CEO of Uber. “By working with Nvidia, we are confident that we can help supercharge the timeline for safe and scalable autonomous driving solutions for the

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Nvidia has announced it has key design wins for autonomous vehicles with car makers such as Toyota, Aurora and Continental. These partners are part of a growing list for Nvidia, and they’re rolling out next-generation highly automated an autonomous vehicle fleets. Jensen Huang, CEO of Nvidia, made the announcements at his opening keynote speech at CES 2025. Nvidia announced today that those companies have joined the list of global mobility leaders developing and building their consumer and commercial vehicle fleets on Nvidia accelerated computing and AI. Toyota, the world’s largest automaker, will build its next-generation vehicles on the high-performance, automotive-grade Nvidia Drive AGX Orin system-on-a-chip (SoC), running the safety-certified Nvidia DriveOS operating system. These vehicles will offer functionally safe, advanced driving assistance capabilities. Nvidia’s Thor chip platform The majority of today’s auto manufacturers, truckmakers, robotaxi and autonomous delivery vehicle companies, tier-one suppliers and mobility startups are developing on Nvidia’s Drive AGX platform and technologies. With cutting-edge platforms spanning from training in the cloud to simulation to compute in the car, Nvidia’s automotive vertical business is expected to grow to approximately $5 billion in fiscalyear 2026. “The autonomous vehicle revolution has arrived, and automotive will be one of the largest AI and robotics industries,” said Huang. “Nvidia is bringing two decades of automotive computing, safety expertise and its CUDA AV platform to transform the multitrillion-dollar auto industry.” Aurora, Continental and Nvidia this week also announced a long-term strategic partnership to deploy driverless trucks at scale, powered by Nvidia Drive. Nvidia’s accelerated compute running DriveOS will be integrated into the Aurora Driver, an SAE level 4 autonomous-driving system that Continental plans to mass-manufacture in 2027. Nvidia Drive Hyperion Other mobility companies adopting Nvidia Drive accelerated compute for their next-generation advanced driver-assistance systems and autonomous vehicle roadmaps include BYD, JLR, Li Auto, Lucid, Mercedes-Benz, NIO, Nuro, Rivian, Volvo Cars, Waabi, Wayve, Xiaomi, ZEEKR, Zoox and many more. Nvidia offers three core computing systems and the AI software essential for end-to-end autonomous vehicle development. One is the Nvidia Drive in-vehicle computer for processing real-time sensor data. The other two are Nvidia DGX systems for training AI models and software stacks, and the Nvidia Omniverse platform running on Nvidia OVX systems for testing and validating self-driving systems in simulation. source

The United Kingdom’s antitrust watchdog on Tuesday said it would launch investigations into three areas of digital activity as the new Digital Markets, Competition and Consumers (DMCC) Act comes into full force — giving regulatory power over major players like Apple and Google. While the Competition and Markets Authority (CMA) did not specify which companies would be investigated, under its strict strategic market status (SMS) designation, only the largest tech firms would be considered. The announcement says two investigations would begin immediately and a third would begin in about six months. Once a company receives SMS designation, the CMA would have the authority to curtail practices like using access to customer data to gain unfair advantage, make it easier for consumers to switch providers, and more. A CMA report released in November called out Apple and Google’s dominant market positions in mobile as potential investigation targets, saying a revenue-sharing agreement between the two companies stifled competition. “We are committed to implementing the regime in a way that is predictable and proportionate, moving at pace whilst respecting fair process,” CMA Chief Executive Sarah Cardell said in a statement. “… The process for designing any interventions will also be participative and transparent, with the aim of keeping innovation-led markets open and bringing firms on the journey with us.” Related:In Global Contest for Tech Talent, US Skills Draw Top Pay The investigations will be complete within the statutory limit of nine months, the CMA said. Significant fines — up to 10% of the company’s global turnover — could be levied if the CMA finds a breach in consumer protection law. US tech firms are facing increasing scrutiny from regulators abroad. The EU’s Digital Markets Act is also taking aim at antitrust concerns, with probes targeting Apple, Google, and Amazon in March. Possible fines could also reach 10% of those companies’ global turnover, potentially costing the companies billions of dollars. CMA’s Impact on M&A, and US Firm Focus In a blog post, lawyers with Morgan Lewis said the UK’s new rules could have a profound impact on potential mergers and acquisitions for the world’s leading tech companies. “The UK CMA has gained a reputation in recent years as an aggressive and impactful antitrust enforcer,” lawyers Joshua Goodman, Omar Shah, R. Ryan Hoak, and Jack Ashfield wrote. “The UK DMCC only bolsters its powers and as such it is more relevant that ever to consider the role of and approach to the UK SMA as part of the global merger review process.” Related:Tracking, Tackling, and Transforming Technical Debt: The New Challenge To AI Critics of newly granted antitrust regulation powers like DMCC say the rules discriminate against US firms and jeopardize investment and cooperation between countries. “Given that the United Kingdom’s digital sector accounted for nearly 1.9 million jobs in 2022 and contributed over [$174 billion] to the UK economy in 2020, the UK government should tread carefully,” writes Meredith Broadbent, a senior adviser at the Center for Strategic & International Studies, in a post. InformationWeek has reached out to Google and Apple for comment and will update with any response. source

By Katryna Perera ( January 7, 2025, 5:38 PM EST) — A Didi Global Inc. investor asked Tuesday to sub in as lead plaintiff in a proposed class action claiming the Chinese ride-hailing giant misrepresented the risks of a disciplinary crackdown from the Chinese government over alleged data security violations, as the suit’s current leader plans to withdraw from the litigation…. Law360 is on it, so you are, too. A Law360 subscription puts you at the center of fast-moving legal issues, trends and developments so you can act with speed and confidence. Over 200 articles are published daily across more than 60 topics, industries, practice areas and jurisdictions. A Law360 subscription includes features such as Daily newsletters Expert analysis Mobile app Advanced search Judge information Real-time alerts 450K+ searchable archived articles And more! Experience Law360 today with a free 7-day trial. source

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Facebook creator and Meta CEO Mark “Zuck” Zuckerberg shook the world again today when he announced sweeping changes to the way his company moderates and handles user-generated posts and content in the U.S. Citing the “recent elections” as a “cultural tipping point,” Zuck explained in a roughly five-minute-long video posted to his Facebook and Instagram accounts this morning (Tuesday, January 7) that Meta would cease using independent third-party fact checkers and fact-checking organizations to help moderate and append notes to user posts shared across the company’s suite of social networking and messaging apps, including Facebook, Instagram, WhatsApp and Threads. Instead, Zuck said that Meta would rely on a “Community Notes” style approach, crowdsourcing information from the users across Meta’s apps to give context and veracity to posts, similar to (and Zuck acknowledged this in his video) the rival social network X (formerly Twitter). Zuck cast the changes as a return to Facebook’s “roots” in free expression, and a reduction in over-broad “censorship.” See the full transcript of his remarks at the bottom of this article. Why this policy change matters to businesses With more than 3 billion users across its services and products worldwide, Meta remains the largest social network to date. In addition, as of 2022, more than 200 million businesses worldwide, most of them small, used the company’s apps and services — and 10 million were active paying advertisers on the platform, according to one executive. Meta’s new chief global affairs officer Joe Kaplan, a former deputy chief of staff for Republican President George W. Bush — who recently took on the role in what many viewed as a signal to lawmakers and the wider world of Meta’s willingness to work with the GOP-led Congress and White House following the 2024 election — also published a note to Meta’s corporate website describing some of the changes in greater detail. Already, some business executives such as Shopify’s CEO Tobi Lutke have seemingly embraced the announcement. As Lutke wrote on X today: “Huge and important change.” Founders Fund chief marketing officer and tech influencer Mike Solana also hailed the move, writing in a post on X: “There’s already been a dramatic decrease in censorship across the [M]eta platforms. but a public statement of this kind plainly speaking truth (the “fact checkers” were biased, and the policy was immoral) is really and finally the end of a golden age for the worst people alive.” However, others are less optimistic and receptive to the changes, viewing them as less about freedom of expression, and more about currying favor with the incoming administration of President-elect Donald J. Trump (to his second non-consecutive term) and the GOP-led Congress, as other business executives and firms have seemingly moved to do. “More free expression on social media is a good thing,” wrote the nonprofit Freedom of the Press Foundation on the social network BlueSky (disclosure: my wife is a board member of the non-profit). “But based on Meta’s track record, it seems more likely that this is about sucking up to Donald Trump than it is about free speech.” George Washington University political communication professor Dave Karpf seemed to agree, writing on BlueSky: “Two salient facts about Facebook replacing its fact-checking program with community notes: (1) community notes are cheaper. (2) the incoming political regime dislikes fact-checking. So community notes are less trouble. The rest is just framing. Zuck’s sole principle is to do what’s best for Zuck.” And Kate Starbird, professor at the University of Washington and cofounder of the UW Center for an Informed Public, wrote on BlueSky that: “Meta is dropping its support for fact-checking, which, in addition to degrading users’ ability to verify content, will essentially defund all of the little companies that worked to identify false content online. But our FB feeds are basically just AI slop at this point, so?” Reached by email, Damian Rollison, Director of Market Insights at AI marketing firm SOCi, also noted that Zuck and Meta appeared by emulating a more libertine approach toward online content moderation championed by X owner Elon Musk: “I think it’s safe to say that no one predicted Elon Musk’s chaotic takeover of Twitter would become a trend other tech platforms would follow, and yet here we are. We can see now in retrospect that Musk established a standard for a newly conservative approach to the loosening of online content moderation, one that Meta has now embraced in advance of the incoming Trump administration. What this will likely mean is that Facebook and Instagram will see a spike in political speech and posts on controversial topics. As with Musk’s X, where ad revenues are down by half, this change may make the platform less attractive to advertisers. It may also cement a trend whereby Facebook is becoming the social network for older, more conservative users and ceding Gen Z to TikTok, with Instagram occupying a middle ground between them.” When will the changes take place? Both Zuck and Kaplan stated in their respective video and text posts that the changes to Meta’s content moderation policies and practices would be coming to the U.S. in “the next couple of months.” Meta will discontinue its independent fact-checking program in the United States, launched in 2016, in favor of a community notes model inspired by X (formerly Twitter). This system will rely on users to write and rate notes, requiring agreement across diverse perspectives to ensure balance and prevent bias. According to its website, Meta had been working with a variety of organizations “certified through the non-partisan International Fact-Checking Network (IFCN) or European Fact-Checking Standards Network (EFCSN) to identify, review and take action” on content deemed “misinformation.” However, as Zuck opined in his video post, “after Trump first got elected in 2016 the legacy media wrote non-stop about how misinformation was a threat to democracy. We tried, in good faith, to address those concerns without becoming the arbiters of