Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Anthropic introduced a new high-end subscription tier for its Claude chatbot today, directly challenging OpenAI’s premium offerings and marking the latest escalation in the race to monetize powerful AI models amid soaring development costs. The new “Max” plan offers professionals two pricing options: $100 per month for five times the usage of Anthropic’s existing $20 Pro plan, or $200 per month for twenty times the usage. The move mirrors OpenAI’s $200 monthly ChatGPT Pro subscription but adds a less expensive middle tier for those who need more than the basic plan but not the full premium experience. This tiered approach shows Anthropic understands how AI is changing professional work. Many users now see Claude as a constant collaborator, not just an occasional tool. The $100 tier serves professionals who use Claude regularly but don’t need full enterprise access. The $200 tier is for those who rely on Claude throughout their workday. The launch comes as AI companies search for sustainable business models to offset the enormous costs of developing and running increasingly powerful large language models. The latest generation of AI systems, including Anthropic’s recently released Claude 3.7 Sonnet, requires vast amounts of computing resources both for training and everyday operation. Anthropic’s new tiered pricing structure includes a free option, the existing $20 monthly Pro subscription, and the new Max plan starting at $100 monthly, which offers up to 20 times more usage for power users. Credit: Anthropic Power users and premium pricing: The economics behind Claude’s $200 tier For the small but growing cohort of “power users” — professionals who have integrated AI assistants deeply into their daily workflows — hitting usage limits represents a significant productivity bottleneck. The Max plan targets these users, particularly those who expense AI tools individually rather than accessing them through company-wide enterprise deployments. The pricing strategy reveals a fundamental shift in how AI companies view their customer base. What began as experimental technology is rapidly stratifying into distinct market segments with dramatically different usage patterns and willingness to pay. Anthropic’s tiered structure acknowledges this reality: casual users can access basic capabilities for free, professionals with moderate needs pay $20 monthly, power users requiring substantial resources invest $100-$200 monthly, and enterprises negotiate custom packages. This segmentation creates a critical “missing middle” solution. Until now, there’s been a vast chasm between individual subscriptions and enterprise contracts, leaving small teams and departments without right-sized options. The $100 tier particularly fills this gap, enabling team leads to expense meaningful AI resources without navigating complex procurement processes. The $200 price point represents a significant bet on AI’s growing indispensability. Few professionals would have considered such an expense justifiable a year ago, but the calculus changes dramatically as these systems become embedded in daily workflows. For a marketer, developer, or analyst billing clients at $150+ hourly, Claude’s ability to accelerate projects by even 10% represents an obvious return on investment. Early access privileges: How Anthropic’s feature pipeline entices premium subscribers Beyond higher usage limits, Max subscribers will receive priority access to upcoming features before they roll out to other users. According to the company, this includes Claude’s voice mode, which is expected to launch in the coming months. This approach reveals Anthropic’s sophisticated product development strategy. Rather than simply charging more for existing capabilities, the company creates a premium experience combining higher capacity with innovation privileges. This mirrors strategies companies like Tesla use, which offers premium customers early access to new autopilot features, creating tangible status value beyond raw specifications. The voice mode tease is particularly significant. Voice interaction represents the next frontier in AI assistance, potentially transforming how professionals engage with Claude throughout their workday. The ability to verbally brief Claude on contexts, request analyses while multitasking, or receive spoken summaries while commuting could dramatically expand the assistant’s utility in professional settings. For Anthropic, this exclusive access model serves multiple purposes: it creates powerful incentives for upgrades, establishes a controlled testing environment for new features and generates valuable feedback from its most engaged users. The company essentially creates a revenue-generating beta program where customers pay for the privilege of shaping product development—a remarkably efficient approach to innovation. Perfect timing: Claude 3.7 Sonnet’s launch creates ideal runway for premium pricing The Max plan’s launch follows just weeks after Anthropic released Claude 3.7 Sonnet, which the company describes as its “most intelligent model to date” and its first “reasoning model” — designed to use more computing power for more reliable answers to complex questions. This sequencing reveals Anthropic’s savvy product marketing strategy. By first demonstrating Claude 3.7 Sonnet’s superior capabilities — particularly in reasoning, coding, and complex information processing — the company created market desire before introducing the premium pricing that makes these advanced features economically sustainable. The reasoning model approach represents a significant technological advancement worth examining. Unlike traditional language models that balance performance across diverse tasks, reasoning models allocate additional computational resources to problems requiring structured thinking and logical analysis. This creates a qualitatively different experience for users tackling complex challenges — an experience Anthropic now argues justifies premium pricing. Dario Amodei, Anthropic’s CEO, alluded to the company’s growing revenue during a CNBC interview in January, though exact figures remain private. Industry sources estimate Anthropic’s annualized revenue hit approximately $1 billion in December 2024, representing nearly tenfold growth year-over-year. The company closed its latest funding round last month at a $61.5 billion valuation. For comparison, OpenAI reportedly told investors its annualized revenue grew by $300 million within just two months of launching ChatGPT Pro, according to documents viewed by TechCrunch. These figures suggest the market for premium AI services is expanding rapidly, with customers demonstrating clear willingness to pay for higher quality and greater capacity. Working with AI all day: How professionals are reimagining their workflows around Claude Anthropic has identified three primary use cases driving high usage: automating repetitive tasks, enhancing capabilities within existing roles, and enabling

Generative AI (genAI) and agentic workflows are roiling technology services markets, overturning the 15-year stability of the prevailing business model. The era defined by time-and-materials pricing, agnostic technology positions, and people-driven business growth is no longer viable. Since the peak growth seen in 2021, which followed years of consistency post-Great Recession, it has become an entirely different story. Starting in 2022, four powerful forces began converging to disrupt the services status quo, forcing providers toward radically different choices and reshaping the sector to deliver what enterprises need now. These forces are: Consolidation and scaling of the core. For 15 years, technology has expanded into every nook and cranny of business, often funded as standalone projects. Now CFOs are pausing discretionary projects and asking their organizations to get more value from existing tech investments. IT responds by transforming the core, scaling platforms, consolidating redundant unused systems, and retiring tech debt. This will lay the foundation for investments in technology-driven growth. For service providers, this shows up as strong “large deal” bookings and weak discretionary bookings. This force could drag on for years. Ecosystems, alliances, and solutions. Enterprises depend on technology partners. Rapid innovation, complex ecosystems, and talent gaps make in-house execution impractical. For service providers, this means that alliance partners are now critical contributors to success. They must develop deep specializations and integrate platforms into solutions. Accenture, Deloitte, and others have long had partner-centric businesses. Others are newly energized: IBM Consulting, which in the past rarely mentioned partners, said that partners were involved in 40% of its deals in 2024. This force will gain even more potency as firms invest in AI computing. The AI effect. As pure knowledge businesses, service providers are on the front lines of genAI-powered disruption. GenAI-powered digital assistants supplement service providers’ teams’ work, augmenting their knowledge, skills, and experience as well as automating their tasks. The impact is more work completed in less time with fewer people — a huge deflationary force in a business that charges by the hour. This force is pushing providers to invest billions in genAI tooling, renegotiate contract deliverables, and build solutions and managed services. Tech’s labor/capital imbalance. Machinery is more predictable and reliable than manual labor. But IT remains a people-constrained activity, where people and skills are gating factors to successful outcomes. In this context, service providers have high motivation to use machinery to make their employees more productive. They invest in reusable software, data, and model assets; preassemble solutions and platforms; and automate as much work as possible, thus shifting the balance away from people and toward capital. The rise of agentic systems and new services-as-software businesses will accelerate this trend. Only Bold Providers Will Survive: Embrace Context And Co-Innovation To compete and establish a new long-term value proposition, providers must cannibalize their existing time-and-materials commercial models, riding the cost curve down and reskilling their workforce while reinventing their offerings and business models for the era of AI computing. Providers with scale and strong balance sheets will thrive and reinvent themselves as post-AI service providers, reconstructed to thrive in the AI computing era; smaller or less nimble providers will struggle. Technology Executives Should Run A New Services Playbook As the ground shifts when it comes to the role and contributions of service providers, technology executives should begin playing by some new rules: Ask for lower costs and faster delivery for complex projects. Factor a provider’s delivery and operating platforms into your selection process. Ask procurement to investigate value-based pricing for service contracts. Retire tech debt and rationalize apps to fund your core transformations. For the in-depth report, click here. source

Is it time to consider a new IT specialty like automation engineering? Jobs site Indeed defines an automation engineer as someone who will “search for ways to simplify activities for employees, consumers and companies by automating specific systems and manufacturing processes, like store checkouts or assembly lines”. These individuals work alongside IT and department managers to develop automation plans and then implement automation into business processes. They use programming languages like Java, C# and Python, and they know how to work with machine actuators and sensors. Most importantly, they possess expertise in the application areas they are asked to automate. In other words, a retail automation expert might have skills in how to automate grocery checkout lines in stores, but they might not know much about how to automate a manufacturing company’s assembly line. In the area of robotics, many of the skills needed for automation engineers carry over for robotics engineers. A primary difference is that a robotics engineer is working on a robot. The goal is to program the robot with the necessary instructions for it to fit into an existing business process. Examples of how working robots are used include programming a robot so it can enter a nuclear facility to perform maintenance, or activating a warehouse robot that can store, pick, and deliver parts from bins throughout the warehouse while successfully navigating around obstacles on the floor. Related:How Today’s CIOs are Upskilling Robotics engineers use languages like C and C# and they commonly work on Linux platforms and must be familiar with the technologies of the particular robotics vendors they are using. Automation and robotics engineers are in high demand in business, although it costs considerably more to recruit an automation engineer (mid-100,000s salary range) than it is to hire a robotics engineer (the mid-point salary is around $80,000/year). Where Do These Engineers Report? Robotics and automation engineers must have the ability to cross-communicate with different departments when they implement solutions. They also need a thorough understanding of the different enterprise systems where the automation or robotics technologies will be deployed. It’s not much of a stretch to see that many of the system knowledge and cross-communicational requirements are exactly what one would find resident with an IT business analyst. The difference is that an automation or robotics engineer would have greater skills in programming, and in working with various mechanical and electronic interfaces. Related:Why IT Leaders Must Prioritize Leading Over Contributing to Projects As a CIO, I once had a project that required automation between our engineering CAD design database and the parts inventory, bill of material and work order systems on the manufacturing floor. There were too may disconnects between engineering and manufacturing. We wanted to eliminate this by integrating and automating information flows between the CAD system and the manufacturing systems. Engineering was running a standalone CAD system on an entirely different platform from what manufacturing was using to run its bills of material, inventory, and work orders. The initial decision was for IT to take the lead in this integration-automation project because IT touched all systems (except for engineering’s standalone CAD system). However, we found out quickly that engineering didn’t want to relinquish any control of its CAD systems for the automation project. We solved this by teaming an engineer from engineering with a programmer-analyst from IT and a manufacturing engineer from, and we got the project done. It wasn’t the easiest project that we ever did. Can IT Avoid Getting Involved? That project with engineering, manufacturing and IT came early in my CIO career, and I learned quickly that automation projects have many different pieces, engage many different departments, and can quickly become as politically charged as they are technically challenging. Related:How to Handle a Runaway IT Development Team I’ve talked to several other CIOs about how to get past politics.  Some are more than happy to just have the departments that want to automate retain their own consultants or hire in the people — and do the work themselves — but I’ve seldom seen this work. Why? Because invariably, the consultant or the engineer that a department brings in has a question about how to integrate with other enterprise systems that IT manages. One way or another, IT will be involved. Is There a Best Approach? From personal experience and from conversations I’ve had with other managers, an optimal approach to automation and robotics when IT works with engineering-oriented departments such as manufacturing, is to place the automation or robotics engineer in the engineering or manufacturing areas. Then the engineers can be savvy on the departments’ business processes as well as on the automation and robotics technologies that are needed. In this scenario, IT would be assisting primarily in system integration. However, if the company is in finance, healthcare, retail, or other non-engineering-oriented businesses, it’s likely that IT might be the best destination for a robotics or automation engineer, because the user departments won’t have the necessary skillset. In all cases, automation and robotics projects require strong collaboration and cooperation between departments and IT. In this way, everyone can be assured that they are moving into each project with a complete and comprehensive knowledge base of the business, the systems, and what they want to automate.  source

By Tracey Read ( April 9, 2025, 3:32 PM EDT) — Pillsbury Winthrop Shaw Pittman LLP has added three attorneys with unique dealmaking experience to its growing Houston office…. 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

By Ryan Harroff ( April 8, 2025, 6:05 PM EDT) — The chief executive officer of a Philadelphia-area information technology staffing firm was charged with failing to collect and pay $2 million in trust fund taxes on behalf of his company and also perjuring himself in his Chapter 13 bankruptcy proceedings…. 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 Researchers at Sentient Foundation have released Open Deep Search (ODS), an open-source framework that can match the quality of proprietary AI search solutions such as Perplexity and ChatGPT Search. ODS equips large language models (LLMs) with advanced reasoning agents that can use web search and other tools to answer questions.  For enterprises looking for customizable AI search tools, ODS offers a compelling, high-performance alternative to closed commercial solutions. The AI search landscape Modern AI search tools like Perplexity and ChatGPT Search can provide up-to-date answers by combining LLMs’ knowledge and reasoning capabilities with web search. However, these solutions are typically proprietary and closed-source, making it difficult to customize them and adopt them for special applications.  “Most innovation in AI search has happened behind closed doors. Open-source efforts have historically lagged in usability and performance,” Himanshu Tyagi, co-founder of Sentient, told VentureBeat. “ODS aims to close that gap, showing that open systems can compete with, and even surpass, closed counterparts on quality, speed, and flexibility.” Open Deep Search (ODS) architecture Open Deep Search (ODS) is designed as a plug-and-play system that can be integrated with open-source models like DeepSeek-R1 and closed models like GPT-4o and Claude. ODS comprises two core components, both leveraging the chosen base LLM: Open Search Tool: This component takes a query and retrieves information from the web that can be given to the LLM as context. The open Search Tool performs a few key actions to improve search results and ensure that it provides relevant context to the model. First, it rephrases the original query in different ways to broaden the search coverage and capture diverse perspectives. The tool then fetches results from a search engine, extracts context from the top results (snippets and linked pages), and applies chunking and re-ranking techniques to filter for the most relevant content. It also has custom handling for specific sources like Wikipedia, ArXiv and PubMed, and can be prompted to prioritize reliable sources when encountering conflicting information. Open Reasoning Agent: This agent receives the user’s query and uses the base LLM and various tools (including the Open Search Tool) to formulate a final answer. Sentient provides two distinct agent architectures within ODS: ODS-v1: This version employs a ReAct agent framework combined with Chain-of-Thought (CoT) reasoning. ReAct agents interleave reasoning steps (“thoughts”) with actions (like using the search tool) and observations (the results of tools). ODS-v1 uses ReAct iteratively to arrive at an answer. If the ReAct agent struggles (as determined by a separate judge model), it defaults to a CoT Self-Consistency, which samples several CoT responses from the model and uses the answer that shows up most often. ODS-v2: This version leverages Chain-of-Code (CoC) and a CodeAct agent, implemented using the Hugging Face SmolAgents library. CoC uses the LLM’s ability to generate and execute code snippets to solve problems, while CodeAct uses code generation for planning actions. ODS-v2 can orchestrate multiple tools and agents, allowing it to tackle more complex tasks that may require sophisticated planning and potentially multiple search iterations. ODS architecture Credit: arXiv “While tools like ChatGPT or Grok offer ‘deep research’ via conversational agents, ODS operates at a different layer—more akin to the infrastructure behind Perplexity AI—providing the underlying architecture that powers intelligent retrieval, not just summaries,” Tyagi said. Performance and practical results Sentient evaluated ODS by pairing it with the open-source DeepSeek-R1 model and testing it against popular closed-source competitors like Perplexity AI and OpenAI’s GPT-4o Search Preview, as well as standalone LLMs like GPT-4o and Llama-3.1-70B. They used the FRAMES and SimpleQA question-answering benchmarks, adapting them to evaluate the accuracy of search-enabled AI systems. The results demonstrate ODS’s competitiveness. Both ODS-v1 and ODS-v2, when combined with DeepSeek-R1, outperformed Perplexity’s flagship products. Notably, ODS-v2 paired with DeepSeek-R1 surpassed the GPT-4o Search Preview on the complex FRAMES benchmark and nearly matched it on SimpleQA. An interesting observation was the framework’s efficiency. The reasoning agents in both ODS versions learned to use the search tool judiciously, often deciding whether an additional search was necessary based on the quality of the initial results. For instance, ODS-v2 used fewer web searches on the simpler SimpleQA tasks compared to the more complex, multi-hop queries in FRAMES, optimizing resource consumption. Implications for the enterprise For enterprises seeking powerful AI reasoning capabilities grounded in real-time information, ODS presents a promising solution that offers a transparent, customizable and high-performing alternative to proprietary AI search systems. The ability to plug in preferred open-source LLMs and tools gives organizations greater control over their AI stack and avoids vendor lock-in. “ODS was built with modularity in mind,” Tyagi said. “It selects which tools to use dynamically, based on descriptions provided in the prompt. This means it can interact with unfamiliar tools fluently—as long as they’re well-described—without requiring prior exposure.” However, he acknowledged that ODS performance can degrade when the toolset becomes bloated, “so careful design matters.” Sentient has released the code for ODS on GitHub. “Initially, the strength of Perplexity and ChatGPT was their advanced technology, but with ODS, we’ve leveled this technological playing field,” Tyagi said. “We now aim to surpass their capabilities through our ‘open inputs and open outputs’ strategy, enabling users to seamlessly integrate custom agents into Sentient Chat.” source

AI is now embedded across nearly every domain of business and life. I’m starting to call this phenomenon the AI effect: the rapid spread of AI into everything, everywhere. It’s a shift that is both promising and pressing — exciting in potential but overwhelming in pace. Clients are increasingly anxious to know what the future holds. Specifically, leaders are asking AI value questions: Are we investing wisely? Are we getting value? How do we measure ROI? Three Ways That AI Is Already Reshaping The World In our vision report Change The Interface; Change The World, we define AI computing and predict how it will change the world. That future is now arriving in three critical ways: Creating AI-advantaged humans. AI-powered personal agents are beginning to act on behalf of individuals. For example, Genspark enables users to have AI make phone calls and automate many other routing tasks — signaling the early emergence of digital doubles. Reinventing the knowledge economy. AI is beginning to unlock and scale human expertise, leading to new business models powered by agentic productivity. Thoughtful AI, a claims automation startup, sells its AI agents based on the number of people that you won’t need to hire. Disrupting tech markets. The surge in demand for AI compute is giving rise to the AI cloud. Google Cloud Platform, once a distant third, is now the fastest-growing public cloud provider — driven in part by AI platform demand and differentiated infrastructure. These effects are building on each other, creating acceleration. I’m currently planning a report on the current and future state of AI computing to explore these trends in depth. What Clients Are Wrestling With Right Now In guidance sessions, I’m helping clients navigate the velocity of AI change. Here are the core challenges I’m seeing: AI value optimization. Clients are under pressure to prove ROI beyond pilots and prototypes. The challenge is balancing fast-moving tech with investment justification and long-term value realization. Getting ready for agentic AI. There’s confusion between automation, AI agents, and agentic systems. Our latest research defines these terms, but clients want more: how to assess maturity, build data readiness, and operationalize AI across teams. AI risk and governance. AI safety has become a board-level concern. Every major vendor is releasing a responsible AI scaling policy as they see that the raw power of emerging agentic systems needs advanced controls. Clients are starting to notice this and are asking me questions about how to prepare. The artificial general intelligence (AGI) question. With public predictions about AGI accelerating, clients are asking about it in my “future of AI” guidance sessions. While a breakthrough could happen anytime, true AGI is not imminent, especially as we see transformer architecture begin to hit a wall (see the latest disappointing Llama 4 results). What’s already emerging is a class of domain-specific super agents that are multimodal and multimodel (e.g., the Genspark example above). These conversations are also shaping my research agenda: separating hype from reality and guiding clients toward practical next steps that prepare them for the future. What’s Next: Building For Scale And Trust As clients move from vision to execution, one theme is becoming central: trust — trust in data, trust in models, and trust in outcomes. Without it, scaling AI — especially in high-stakes domains — stalls. As I highlight in my upcoming report, “The Top 10 Emerging Technologies In 2025,” trust will be the deciding factor in whether organizations realize the full value of the AI effect. That’s why Forrester Decisions for Data, AI & Analytics was created: to offer clients more than just vision but also best practices, how-tos, and templates to thrive in this volatile and chaotic time. Let’s Continue The Conversation If you’re a Forrester client, I encourage you to book a guidance session or inquiry. I’d be glad to share more of our latest thinking and help shape your strategy. If you’re not a client but have a compelling story or challenge, let’s connect. I’d welcome the opportunity to learn from you — and will happily share what we’re learning in return. Please read Change The Interface; Change The World, Turn Your Proprietary Knowledge Into AI Advantage, and Agentic AI Is Rising And Will Reforge Businesses That Embrace It for more forward-looking insight and practical advice on how to prepare for the future. Stay tuned for more research on our top emerging technologies for 2025, AI value, AI computing, and AGI. source

美聯儲穆薩勒姆表示，因企業和家庭將要適應被新進口關稅推高的物價，美國經濟成長可能“大幅”下滑至趨勢水平下方，失業率將在年內上升。 穆薩勒姆表示：“我沒有一個衰退的基線，但我認為經濟增長可能會大大低於趨勢，”他估計增長率在2%左右。他表示，“雙向的風險都將成為現實，”高於預期的關稅給物價帶來壓力、信心下降和近期股市大幅下跌可能抑制支出，打擊家庭財富、物價上漲將造成影響，這些因素加在一起導致經濟增長放緩。 LinkedIn Email Facebook Twitter WhatsApp The post 美聯儲穆薩勒姆認為美國經濟增長可能會大大低於趨勢 appeared first on VeriMedia. source

According to StatCounter, Android accounted for 71.72% of the world’s mobile operating systems as of February 2025. That’s an overwhelming amount of devices — and in turn, a massive amount of passwords and accounts on each device. While you can still use sticky notes to keep track of passwords, writing them down isn’t a secure way to manage your sensitive credentials. This is where password managers come in. Password managers encrypt and organize your passwords, allowing you to easily access important logins without sacrificing security. For businesses that mainly use Android devices — you’re in luck. There are a number of high quality password managers on Android that are worth your time and money. In this article, we look at the best password managers for Android devices. 1 NordPass 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), Enterprise (5,000+ Employees) Micro, Small, Medium, Large, Enterprise Features Activity Log, Business Admin Panel for user management, Company-wide settings, and more 2 Dashlane 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), Enterprise (5,000+ Employees) Micro, Small, Medium, Large, Enterprise Features Automated Provisioning 3 ManageEngine ADSelfService Plus 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 Access Management, Compliance Management, Credential Management, and more Top password managers for Android comparison All the Android password managers featured on this list have the essentials: high-end encryption, a password generator, and password autofilling capabilities. While they have a ton of similarities, there are various feature focuses per password manager depending on your needs. Software Password health monitoring Password sharing Standout feature Starting Personal account price Starting Business account price Bitwarden4.6 / 5 stars Yes (Vault Health reports) Yes open-source platform and free version $0.83 per month $4 per month, per user NordPass4.6 / 5 stars Yes (Password Health) Yes Affordable plans for smaller teams $1.69 per month $1.79 per month, per user 1Password4.3 / 5 stars Yes (Watchtower) Yes Ease of use $2.99 per month $19.95 per month for 10 users Keeper4.4 / 5 stars Yes (Security Audit) Yes Business features $2.92 per month $2.00 per month, per user Dashlane4.4 / 5 stars Yes (Password Health) Yes Bang-for-buck family plan $4.99 per month $8 per month, per user Bitwarden: Best overall password manager for Android Image: Bitwarden Bitwarden is a highly secure password manager that’s a fan-favorite amongst Android users — and for good reason. Like Android, Bitwarden is open-source which means that its source code is publicly available. This makes it easier to track vulnerabilities in its code and prevent unwanted exploits. In addition, Bitwarden has one of the best free plans in the password manager space, offering unlimited password storage on an unlimited number of devices. Add to that its simple user interface, affordable paid plans, and clean security reputation, Bitwarden should be your go-to password manager for Android. Bitwarden’s Android app interface. Image: Luis Millares Why I chose Bitwarden Bitwarden is my best overall password manager on Android for its high quality mix of affordability and security — all built on its open-source architecture. It has a sterling security reputation, which is also crucial for software that takes hold of your most sensitive data. Bitwarden’s desktop app counterpart. Image: Luis Millares Pricing Bitwarden has a free version and paid plans for both individual and business users. Here’s the pricing rundown of their paid subscriptions: Premium: $0.32 per month. Families: $3.33 per month, up to six users. Teams: $4 per month, per user. Enterprise: $6 per month, per user. Customized plan: Contact Bitwarden for quotation. Features Open-source. Encrypted text and file-sharing. Free version with unlimited password storage. Zero knowledge. Pros and cons Pros Cons Clean security reputation. Affordable pricing across plans. Popular pick among Android users. Doesn’t have tons of extra features. If you want to learn more, read my full Bitwarden review here. NordPass: Best for smaller teams Image: NordPass NordPass is Nord Security’s flavor on password management that brings with it the same focus on security and useability as their popular NordVPN solution. For security, NordPass is the only Android password manager in our rundown that uses XChaCha20 encryption. This is a more modern algorithm that, they say, provides future-proof security, compared to the industry standard AES-256 cipher. It also operates on zero-knowledge principles, which means only the end-user has access to their data. Aside from this, NordPass on Android also lets you store passkeys, notes, credit card info, and other important information in your vault. NordPass on Android. Image: Luis Millares Why I chose NordPass I chose NordPass specifically for its wide range of plan options, which I envision can be beneficial to smaller teams or businesses on a tighter budget. It’s the only password manager on this list that offers both one and two-year plan options, which can help with lowering monthly costs in the long run. NordPass on Windows. Image: Luis Millares Pricing NordPass offers a free plan as well as one and two-year paid subscriptions for its Personal and Business tiers. Below is an overview of the prices for each plan and tier. NordPass Personal & Family plans: Premium 1-year: $1.69 per month. Premium 2 years: $1.29 per month. Family 1-year: $3.69 per month, six users. Family 2 years: $2.79 per month, six users. NordPass Business plans: Teams 1-year: $1.99 per user, per month; 10 users. Teams 2 years: $1.79 per user, per month; 10 users. Business 1-year: $3.99 per user, per month; five to 250 users. Business 2 years: $3.59 per user, per month; five to 250 users. Enterprise 1-year: $5.99 per user, per month; unlimited users. Enterprise 2 years: $5.39 per user, per month; unlimited users. Features XChaCha20 encryption algorithm. Password health and data breach scanning. Free version. Pros and cons Pros Cons Affordable individual and business subscriptions.

VISIONARY HOLDINGS INC. News Correction Released on March 10, 2025,   Visionary Holdings Inc., a public Company, trading on the NASDAQ exchange symbol:” GV” Hereby informs its Shareholders and the Public with the following information:   It has become clear that Visionary Holdings Inc. was targeted by a sophisticated impersonation scheme, in which an individual falsely claimed to represent Al Fardan Group LLC.  The documents and correspondence we received, which at the time appeared credible enough to make public information, have now been determined to be falsified.  Based on these materials, Visionary paid a substantial retainer to initiate a due diligence process and move forward with what we believed to be a legitimate transaction. The information published by “GV” stated that it had reached an agreement that $1 – Billion in financing or an Intent Agreement with Al Fardan Group LLC.was in place and could be relied upon. According to the intended Agreement, Al Fardan Group LLC. was to invest $1 billion intoour company for the development of the new energy vehicle industry. This Intent Agreement was signed through the introduction of the former chairman of GV, Wei De Zhai. Later, Ms. Fan Zhou, the current Chairman of Visionary Holdings Inc., personally visited the headquarters of Al Fardan Group LLC. for verification. This is when it was discovered to be falsified. Upon learning of this information on March 26th, 2025, due to Ms. Fan Zhou actually going to the location offices, the company immediately launched an internal investigation and engaged external legal and technical experts to thoroughly trace and verify the origin of the communications that led to the publication of the press release.   We now understand that Mr. Abid Nazir Mian, the individual who claimed to represent Al Fardan Group, had no affiliation whatsoever, and was acting without authorization.   Meanwhile, the company promptly held an extraordinary general meeting of shareholders and dismissed the Board Members who were derelict in their duties regarding this matter. The new Board of Directors hereby made this information public for clarification of the facts. We hereby extend our sincere apologies to investors. At the same time, Visionary Holdings Inc., has also initiated legal procedures and reported the case to relevant institutions in Canada and the United States, aiming to bring the lawbreakers to justice.   Going forward the newly appointed Board of Directors of Visionary Holdings Inc., will always adhere to the principle of operating with integrity. We will approach information disclosure with a more rigorous attitude, continuously improve the corporate governance and internal control systems, and earnestly protect the rights and interests of investors and partners. Once again, we deeply apologize for the inconvenience caused by this incident and thank you all for your understanding and support. Visionary Holdings, Inc. April 9, 2025   LinkedIn Email Facebook Twitter WhatsApp source