Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Transformer-based large language models (LLMs) are the foundation of the modern generative AI landscape. Transformers aren’t the only way to do gen AI, though. Over the course of the last year, Mamba, an approach that uses Structured State Space Models (SSM), has also picked up adoption as an alternative approach from multiple vendors, including AI21 and AI silicon giant Nvidia.  Nvidia first discussed the concept of Mamba-powered models in 2024 when it initially released the MambaVision research and some early models. This week, Nvidia is expanding on its initial effort with a series of updated MambaVision models available on Hugging Face. MambaVision, as the name implies, is a Mamba-based model family for computer vision and image recognition tasks. The promise of MambaVision for enterprise is that it could improve the efficiency and accuracy of vision operations, at potentially lower costs, thanks to lower computational requirements. What are SSMs and how do they compare to transformers? SSMs are a neural network architecture class that processes sequential data differently from traditional transformers.  While transformers use attention mechanisms to process all tokens in relation to each other, SSMs model sequence data as a continuous dynamic system. Mamba is a specific SSM implementation developed to address the limitations of earlier SSM models. It introduces selective state space modelling that dynamically adapts to input data and hardware-aware design for efficient GPU utilization. Mamba aims to provide comparable performance to transformers on many tasks while using fewer computational resources Nvidia using hybrid architecture with MambaVision to revolutionize Computer Vision Traditional Vision Transformers (ViT) have dominated high-performance computer vision for the last several years, but at significant computational cost. Pure Mamba-based approaches, while more efficient, have struggled to match Transformer performance on complex vision tasks requiring global context understanding. MambaVision bridges this gap by adopting a hybrid approach. Nvidia’s MambaVision is a hybrid model that strategically combines Mamba’s efficiency with the Transformer’s modelling power.  The architecture’s innovation lies in its redesigned Mamba formulation specifically engineered for visual feature modeling, augmented by strategic placement of self-attention blocks in the final layers to capture complex spatial dependencies. Unlike conventional vision models that rely exclusively on either attention mechanisms or convolutional approaches, MambaVision’s hierarchical architecture employs both paradigms simultaneously. The model processes visual information through sequential scan-based operations from Mamba while leveraging self-attention to model global context — effectively getting the best of both worlds. MambaVision now has 740 million parameters The new set of MambaVision models released on Hugging Face is available under the Nvidia Source Code License-NC, which is an open license. The initial variants of MambaVision released in 2024 include the T and T2 variants, which were trained on the ImageNet-1K library. The new models released this week include the L/L2 and L3 variants, which are scaled-up models. “Since the initial release, we’ve significantly enhanced MambaVision, scaling it up to an impressive 740 million parameters,” Ali Hatamizadeh, Senior Research Scientist at Nvidia wrote in a Hugging Face discussion post. “We’ve also expanded our training approach by utilizing the larger ImageNet-21K dataset and have introduced native support for higher resolutions, now handling images at 256 and 512 pixels compared to the original 224 pixels.” According to Nvidia, the improved scale in the new MambaVision models also improves performance. Independent AI consultant Alex Fazio explained to VentureBeat that the new MambaVision models’ training on larger datasets makes them much better at handling more diverse and complex tasks.  He noted that the new models include high-resolution variants perfect for detailed image analysis. Fazio said that the lineup has also expanded with advanced configurations offering more flexibility and scalability for different workloads. “In terms of benchmarks, the 2025 models are expected to outperform the 2024 ones because they generalize better across larger datasets and tasks, Fazio said.  Enterprise implications of MambaVision For enterprises building computer vision applications, MambaVision’s balance of performance and efficiency opens new possibilities Reduced inference costs: The improved throughput means lower GPU compute requirements for similar performance levels compared to Transformer-only models. Edge deployment potential: While still large, MambaVision’s architecture is more amenable to optimization for edge devices than pure Transformer approaches. Improved downstream task performance: The gains on complex tasks like object detection and segmentation translate directly to better performance for real-world applications like inventory management, quality control, and autonomous systems. Simplified deployment: NVIDIA has released MambaVision with Hugging Face integration, making implementation straightforward with just a few lines of code for both classification and feature extraction. What this means for enterprise AI strategy MambaVision represents an opportunity for enterprises to deploy more efficient computer vision systems that maintain high accuracy. The model’s strong performance means that it can potentially serve as a versatile foundation for multiple computer vision applications across industries. MambaVision is still somewhat of an early effort, but it does represent a glimpse into the future of computer vision models. MambaVision highlights how architectural innovation—not just scale—continues to drive meaningful improvements in AI capabilities. Understanding these architectural advances is becoming increasingly crucial for technical decision-makers to make informed AI deployment choices. source

Terminology Throughout this report, religious switching refers to a change between the religious group in which a person says they were raised (during their childhood) and their religious identity now (in adulthood). The rates of religious switching are based on responses to two survey questions we asked of adults ages 18 and older: “What is your current religion, if any?” “Thinking about when you were a child, in what religion were you raised, if any?” The responses to these two questions allow us to calculate what percentage of the public has left a religious group (or “switched out”) and what percentage has entered (or “switched in”). This kind of switching can take place without any formal rite or ceremony. We have analyzed switching into and out of five widely recognized, worldwide religions to allow for consistent comparisons around the globe. Specifically, this report analyzes change between the following groups: Christianity, Islam, Judaism, Buddhism, Hinduism, other religions, religiously unaffiliated adults, and those who did not answer the question. For example, someone who was raised Buddhist but now identifies as Christian would be considered as having switched religions – as would someone who was raised Christian but is now unaffiliated. However, switching within a religious tradition, such as between Catholicism and Protestantism, is not captured in this report. (Refer to Pew Research Center’s 2023-24 Religious Landscape Study for an analysis of switching in the United States that does count some switching within Christianity. Read “4 facts about religious switching within Judaism in Israel” for an analysis of switching within Judaism.) Religiously unaffiliated refers to people who answer a question about their current religion (or their upbringing) by saying they are (or were raised as) atheist, agnostic or “nothing in particular.” This category is sometimes called “no religion” or “nones.” Other religions is an umbrella category. It contains a wide variety of religions that are not in the other categories and that have survey sample sizes too small to analyze separately in most countries. This includes Sikhism, Jainism, the Baha’i faith, African traditional religions, Native American religious traditions, and others. Disaffiliation rates refer to the percentage of adults who say they were raised in a religion but are now religiously unaffiliated (or have no religion). Net gains/losses are the differences between the percentage of survey respondents who say they were raised in a particular religious category (as children) and the percentage who identify with that same category at the time of the survey (as adults). The “net” gain or loss takes into account both sides of the equation – those who have left and those who have entered the group. Retention rates show, among all the people who say they were raised in a particular religious group, the percentage who still describe themselves as belonging to that group today. Accession rates (also called entrance rates) show, among all the people who describe themselves as belonging to a particular religious group today, the percentage who were raised in some other group. This section takes a closer look at religious switching into and out of Christianity by reviewing where Christianity has had the largest net losses, what percentage of adults who were raised Christian are still Christian (i.e., retention rates), which religious groups people who left Christianity have switched into, and where Christianity has the largest shares of new entrants (i.e., the highest accession rates). Of the 36 countries surveyed, 27 have sufficient sample sizes of Christians to allow analysis of religious switching into and out of Christianity. Net losses for Christianity More people have left Christianity than have joined it in many of the 27 countries analyzed. Spain has the largest net losses for Christians from religious switching (in proportion to the size of its population) of any country surveyed. Remaining Christian In nearly all countries, majorities of Christians have retained their religion. This is especially true in the Philippines, Hungary and Nigeria, where nearly all people who say they were raised Christian are still Christians as adults. Leaving Christianity Most who have left Christianity no longer identify with any religion, saying they are now atheist, agnostic or have no religion in particular. In some Asian countries, small shares of those raised Christian now identify as Buddhists. Entering Christianity Singapore and South Korea have relatively high rates of “accession,” or entrance, into Christianity, with about four-in-ten or more Christian adults in these countries saying they were raised in another religion or with no religion. However, Christians remain a minority in both countries: 18% of Singaporeans and 33% of South Koreans currently identify as Christian. Among those who have switched into Christianity, many say they were raised Buddhist or without a religion. Where has Christianity experienced the largest net gains and losses from religious switching? In many countries surveyed, more people were raised as Christians and have left Christianity than have become Christians after being raised in some other tradition or without a religious affiliation. In other words, Christianity has experienced an overall or “net” loss in adherents due to religious switching in many places. For example, Spain has the largest net losses for Christians in percentage terms (as a proportion of the country’s total adult population) of the 27 countries analyzed. The vast majority of all Spanish adults surveyed (87%) say they were raised Christian. But far fewer (54%) describe themselves as Christians today – a net loss for Christianity of one-third of all Spanish adults (that is, 33% of the total adult population, not just of current Christians). This loss has occurred because 36% of Spanish adults have left Christianity (i.e., they were raised Christian but no longer identify as such) while just 3% of Spanish adults have entered Christianity (i.e., they identify as Christians today but say they were not raised that way). Even in South Korea – the country with the largest share of adults raised outside of Christianity who now identify as Christian – more people have left Christianity (19% of all South Korean adults) than have entered Christianity

B2B buyers rarely act alone. They are part of large, complex buying groups that rely on a network of trusted sources throughout the decision-making process. Forrester’s B2B Trust research delves into these preferences, offering insights that are invaluable for shaping marketing and sales strategies and influencer relations programs. We find that B2B buyers have distinct preferences for the sources of information they trust most (and least) which shapes who they turn to for insights and guidance: Core insiders lead as trusted information sources. Familiarity breeds trust, not contempt. The most trusted sources for B2B buyers are coworkers and management within an organization, with 82% of buyers saying they are trusted. Close behind are vendors they currently work with, trusted by 79% of respondents. This reveals a strong incumbent advantage, illustrating a preference for the “devil you know” over the uncertainty of new relationships. This pattern suggests a defensive, risk-avoidant approach to change, emphasizing the importance of existing relationships in the B2B landscape. Independent experts come next. Beyond their immediate inner circle, B2B buyers also value the insights of independent experts: industry peers, analysts, and even vendor executives and customers fall into this category, with trust levels ranging from 66% to 72% of respondents. These figures underscore the importance of authoritative voices that offer privileged insights or firsthand experience, free from the perceived bias of direct sales efforts. Other outsiders are the lowest trusted sources. Our research indicates a more cautious approach to sources perceived as having biased interests. Salespeople from vendors, news media, and government officials garner lower levels of trust, with social media influencers at the bottom with only 44% trust. This skepticism reflects a broader trend of declining trust in traditional institutions. Leverage Trust In Marketing And Sales Strategies Understanding these trust dynamics is crucial for developing effective B2B marketing and sales strategies. Marketers should focus their influencer relations programs on the most trusted sources, namely core insiders like coworkers and current vendors, followed by independent experts. Outsiders, while less trusted, still play a role in the broader strategy, serving as channels to amplify the messages from more trusted sources. Sales should heed similar advice and focus on leveraging and promoting information from more trusted sources whenever possible. Bring A Strategic Focus On Trusted Sources For B2B marketers, aligning with trusted insiders and independent experts offers a pathway to gaining the confidence of potential buyers. By focusing on building relationships with these key influencers (not the social media ones), marketers can ensure that their messages are more likely to be received positively. B2B marketing leaders should ensure that trusted preferences are built into buyer persona development and that influencer relations programs are an active and vital part of campaigns. In the same way, content marketing teams should work directly and indirectly with trusted sources and include their perspectives. Make it your goal to create a chorus of voices that builds a positive consensus among buyer groups. You can learn more about who buyers trust and how to influence these influencers at Forrester’s B2B Summit North America. See you there! source

Image: Pressmaster/Envato Elements By 2030, 70% of the skills professionals use in most jobs will change, thanks in large part to AI, according to a new study by LinkedIn. AI literacy tops LinkedIn’s list of 15 Skills on the Rise in the U.S.; number 10 is Large Language Model (LLM) Development & Application. The study also revealed that professionals entering the workforce are on track to hold twice as many jobs over their careers compared to 15 years ago. More than 10% of professionals hired today have job titles that did not even exist in 2000 — and in the U.S., that figure jumps to 20%. One of the hottest emerging roles in 15 countries is Artificial Intelligence Engineer, LinkedIn’s study about skills on the rise found. More must-read AI coverage Top 15 skills on the rise From LinkedIn’s new report, here are the top 15 skills that are on the rise. AI literacy Conflict mitigation Adaptability Process optimization Innovative thinking Public speaking Solution-based selling Customer engagement & support Stakeholder management Large language model (LLM) development & application Budget & resource management Go-to-Market (GTM) strategy Regulatory compliance Growth strategy Risk assessment For each skill, Linkedin details why it’s on the rise, the most common related job titles, and the most common relevant industries. SEE: The Ultimate Artificial Intelligence & Machine Learning E-Degree Bundle from TechRepublic Academy Professionals are heeding the call to learn more skills The study noted some positive news: Professionals are working to keep pace. There has been a 140% increase in the pace at which LinkedIn members add new skills to their profile since 2022, according to the report. This includes a rise in technical skills and soft skills such as communication and leadership. Organizations are investing in upskilling The LinkedIn Work Change report from January 2025 found that over the past two years, 51% of businesses that adopted generative AI reported a revenue increase of 10% or more. It comes as no surprise that 88% of C-suite leaders said helping their workers develop AI skills is important over the next year. Another priority for 38% of global C-suite executives when considering entry-level candidates for their organizations is agility and the ability to move through different roles while upskilling, the report noted. However, the highly sought-after combination of AI and soft skills “remains elusive for many companies,” the report found. Communication has consistently been one of the most sought-after skills by employers and was the No. 1 most in-demand skill in 2024, according to the report. source

Image: Google Google has officially unveiled the Pixel 9a, which it claims boasts the best camera among all smartphones under $500. The Pixel 9a is the most durable in Google’s lineup and offers the longest battery life of any Pixel phone to date. The Pixel 9a is set to launch in April. As expected, Google has packed the device with advanced artificial intelligence features, and the Pixel 9a is no exception. It introduces AI-powered photography capabilities, which may stir controversy, especially following Samsung’s infamous “fake moon” debacle. Still, Google spotlights several compelling features for group photography, including the ability to merge multiple shots from different cameras, ensuring every subject is included while allowing users to select the best facial expressions from a series of images. The phone introduces a suite of AI-powered editing tools that enable users to tweak image elements — such as altering colors or removing objects altogether. More Google news & tips AI-powered features and Gemini integration Gemini, Google’s proprietary AI chatbot, is built into the Pixel 9a, so it works with pre-installed apps like Maps and YouTube to provide directions, recommendations, summaries, natural language searches, and more. The Pixel 9a comes with Gemini Nano, Google’s most lightweight AI model, and Gemini Live, which allows you to speak to the AI assistant à la Siri. Later this month, Gemini Advanced subscribers will be able to share their screen or camera feed with Gemini Live so they can discuss what they are seeing. Camera and hardware upgrades The rear camera has two lenses: a 48MP main camera and a 13MP ultrawide version. For comparison, Apple’s iPhone 16e features a 48MP camera but no wide-angle lens and is priced higher at $599. The Pixel 9a will be the first A-series device, Google’s budget-friendly line, to come with Macro Focus for detailed close-ups and, unlike the Pixel 9, doesn’t have a camera bump so will rest flatly on a table. The Pixel 9a is powered by Google Tensor G4, the company’s fastest and most efficient chip, and the base model will have 8GB of RAM and 128GB of storage. It has a 6.3-inch scratch-resistant Actua display and 2,700 nits of brightness, outdoing the Pixel 8a’s measly 6.1-inches and 2,000 nits. SEE: How to Break a Phone: Common Causes of Phone Damage Battery, durability, and pricing Google boasts that the Pixel 9a has a battery life of 30 hours on normal mode and over 100 hours on Extreme Battery Saver. It has seven years of operating system, security, and other software updates guaranteed, rubbing in the face of iPhone users who only get five. The durability rating has been upgraded from IP67 to IP68, meaning it can now withstand immersion in water of depths up to 1.5 metres for 30 minutes, rather than one metre. Google has introduced a brand new colourway for this device called Iris, a blueish-purple, but it will also come in Peony (pink), Porcelain (white), and Obsidian (black). The base version comes in at $499, and a 256GB version will be available for $599. For comparison, the iPhone 17 Air, Apple’s upcoming affordable option, is rumoured to be priced at about $900. source

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Online meetings used to be much the same as their physical world counterparts.  With the introduction of generative AI, online meeting platforms began to add new insights, including voice transcription services. Platform vendors, including Microsoft Teams, Google Meet and Cisco WebEx, have steadily integrated capabilities that go beyond what in-person physical meetings can provide. Now in the emerging era of agentic AI, online meetings are poised to diverge even further with a new wave of innovations. Zoom recently announced its agentic AI efforts which aims to create the paradigm shift from meetings to milestones. Microsoft has added copilot actions which can integrate with its Microsoft Teams service helping users inside of meetings to get insight and connect with other Microsoft services. Cisco has been steadily expanding its AI capabilities in Webex, and announced a Webex AI agent at the end of 2024 that helps with contact center deployments. Another firm that has been particularly active in the space is Otter AI, which is somewhat differentiated in that it is not directly tethered to any specific online meeting vendor platform. While Otter first made its mark as an AI-powered voice transcription service, it has added an AI assistant called Otter Pilot, an AI chat assistant, and a series of meeting capabilities known as Meeting GenAI. Today, Otter is going a step further, with its foray into agentic AI. While some of the agentic AI features that Otter is adding are not unique, it is doing at least one thing that isn’t yet part of every agentic AI meeting technology. Otter AI is now being integrated as an entity inside of a meeting that can actually respond by voice to queries.  No longer is the AI an external participant accessible just via a chat window; AI is now a live entity that is literally part of the meeting. The rise of AI meeting agents: Beyond silent observers For the last several years, AI meeting assistants have been passive observers—transcribing conversations, creating summaries and allowing post-meeting queries. Otter is now changing this dynamic with its AI Meeting Agent, which can actively participate in conversations when summoned. “The new AI meeting agent we’re building will be able to help you with voice in real-time meetings,” Sam Liang, CEO of Otter AI told VentureBeat. “During the meeting, you can say, ‘Hey Otter,’ and ask it questions.” In a live demonstration with VentureBeat, Liang showed how the agent could answer factual questions, provide meeting summaries and even schedule follow-up meetings—all through voice commands during an active conversation.  What makes this particularly powerful is the agent’s ability to connect to a company’s knowledge ecosystem. “This agent can become a domain expert,” Liang noted. “When you’re having a meeting, it has almost infinite knowledge from the internet, but this agent also has knowledge about your enterprise.” Autonomous agents: When AI runs the meeting Taking agentic capability a step further, Otter is also launching an autonomous SDR (Sales Development Representative) agent that can independently conduct entire meetings without human intervention. This agent greets website visitors, conducts product demonstrations and schedules follow-up meetings with human sales representatives. “We cannot hire a million human agents to answer questions, but we built this Otter SDR agent that functions like a sales development representative who can greet every single visitor and give them a live demo,” Liang said. The use of chatbots and avatar-based systems is not new. Liang argued that what distinguishes his company’s technology from existing avatar-based solutions is its ability to conduct multimedia product demonstrations in real time. The autonomous agent can share screens, demonstrate product features and respond to specific questions about functionality and pricing. The technical architecture of agentic AI for meetings Agentic AI is an overloaded and somewhat overhyped term in the industry today overall. Functionally agentic AI is about enabling actions, which can be done by combining multiple models with a tool like LangChain or by using the function-calling capabilities present in many models. Liang has an even more nuanced definition for agentic AI. “Agents in general are a more sophisticated AI system that can break down a large and complicated task into smaller tasks,” he said. “It can do reasoning and it can do some planning to perform a task.” Otter is not using LangChain but has developed its own custom technology specifically designed for the challenges of multi-speaker voice environments. The technical architecture combines both public knowledge retrieval and proprietary enterprise information through a custom RAG (Retrieval-Augmented Generation) implementation. This enables the agent to understand company-specific information like employee names, project terminology and internal acronyms. The future of meeting intelligence isn’t just agentic AI What agentic AI is bringing to online meeting platforms represents a powerful new set of capabilities for organizational efficiency. For decades, organizational efficiency experts have warned about the risks of wasted time in meetings. Modern AI-powered platforms are changing that risk. Last week Zoom’s CTO told me that his goal was to move the technology from meetings to milestones, where the output of a meeting isn’t just another meeting but actionable things that will benefit the organization. While agentic AI can create workflows, there is still also benefit in regular AI assistants that are not actually agentic. There will still be standalone AI assistants and fully agentic ones and that’s a good thing, according to Anurag Dhingra, SVP & GM, Enterprise Connectivity and Collaboration at Cisco.  “While AI agents act as autonomous do-ers and AI assistants serve as prompted helpers, both offer benefits in boosting productivity and enhancing overall collaboration,” Dhingra told VentureBeat. “It’s not a matter of choosing one over the other but rather leveraging their combined strengths to create environments where teams can focus on innovation and strategic decision-making.” What is also starting to happen is more interoperability across different platforms. For example, Cisco’s AI Assistant will work with workflow applications such as Salesforce, ServiceNow and Outlook. Strategic

A new survey found that more than half (56%) of respondents say it is very or critically important to share the rewards that AI creates with workers, yet most organizations (77%) aren’t doing anything meaningful about it. Leaders are still figuring out what “fair” looks like in an AI-enabled workplace, according to Deloitte’s 2025 Global Human Capital Trends report. Compensate workers or AI? Only 23% of organizations are doing something meaningful to share the rewards AI creates with workers, the Deloitte report said. The dilemma leaders are grappling with includes questions such as: “Should an employee continue receiving rewards after their expertise is embedded into a digital agent? Should productivity gains go toward higher wages, shorter workweeks, or something else?” Kyle Forrest, future of HR leader at Deloitte Consulting, told TechRepublic. Some organizations are sharing productivity gains with frontline workers through financial incentives, he said. “Some use AI efficiencies to support four-day workweeks, while others invest in personalized coaching, talent marketplaces, and stretch assignments that treat every worker as ‘high potential,’ not just a select few.” Do employees think of AI as a coworker? Deloitte’s research found a “possible era of convergence” between humans and machines. For example, six in 10 workers already think of AI as a coworker. The report pointed to signs of this, including: Technology is becoming more human with more human-like interfaces. Robots increasingly resemble and mimic humans. Digital agents are acting on people’s behalf. Humans are teaching AI, and AI is teaching humans. This means organizations will have to rethink how they can help their employees continue to thrive in a world where AI is reshaping work and how it is done. Deloitte recommended that organizations revise the employee value proposition (EVP) to realize both human and business outcomes “as AI becomes increasingly intertwined with workers.” The report, based on input from nearly 10,000 business and human resources leaders in 93 countries, stresses that “Technology’s value does not come from replacing human labor; it’s working more closely than ever with humans, amplifying their ability to discover and capture opportunities for innovation and growth.” Nearly three-quarters of workers and leaders agree it’s critical to prioritize human capabilities, and a similar number believe organizations should do more to connect people with opportunities to build experience, the research found. “That’s a powerful foundation for change,’’ Forrest said. Top concerns about AI’s “silent impacts” While AI often does easy, rote work, it may also reduce one-on-one interactions, contributing to loneliness and isolation, according to the report. It can also contribute to burnout. The Deloitte report recommends that organizations’ EVPs “incorporate a clear understanding of AI’s impact on work, workers, and people’s relationship with employers.” There is a “major opportunity” in how companies can reimagine the employee value proposition in the age of AI, Forrest said. “Over 70% of workers and managers say they’re more likely to stay with an organization that helps them thrive in an AI-powered world,’’ he said. “That’s a clear call to action: When companies use AI to elevate people, not just productivity, they can build loyalty, trust, and long-term value.” source

Expansion of project scope during the migration Weaknesses in project management  Underestimated testing and data migration phases   Revision loops for concepts and processes Decision-making  issues Failure due to misjudgments According to study director and Horváth partner Christian Daxböck, many problems during the transition are rooted in an incorrect program setup. The complexity of the project and the required resources are underestimated, while organizational competence is overestimated. “This mismatch leads to the enormous discrepancies between plan and results,” he says.   Another problem, according to Daxböck, involves prioritization: Too many goals are classified as equally important and should therefore, at best, be addressed simultaneously, which is ultimately also a consequence of inadequate project management.   source

By Hailey Konnath ( March 26, 2025, 11:34 PM EDT) — A Michigan federal judge on Wednesday refused to throw out a white male consultant’s suit alleging that IBM threatens to punish executives if they don’t meet diversity goals, finding that, at least at this stage in the litigation, he’s offered enough facts to support a “reverse discrimination” claim…. 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