By Nadia Dreid ( April 1, 2025, 9:12 PM EDT) — Chinese-Americans have been receiving calls from bad actors attempting to line their own pockets by posing as insurance company employees and government officials in order to get personal information or cash payments, the FCC is warning…. 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

Image: Google All enterprise users of Gmail can now easily apply end-to-end encryption to their emails. Prior to today, this was a luxury reserved for big businesses with significant IT resources, but Google recognises that email attacks are on the rise across the board. Starting today, Gmail users can send end-to-end encrypted emails to others within their organisation; in the coming weeks, they will also be able to send encrypted emails to Gmail inboxes outside their organisation, with support for all email inboxes expected later this year. To get early access for E2EE emails in Gmail, fill out Google’s Pre-General Availability Test Application. How users and IT can use E2EE in Gmail Emails sent with Gmail’s end-to-end encryption are extremely secure because only the sender has control over the encryption key, which is stored outside of Google’s infrastructure. Users can click the padlock by the Bcc button and press Turn On under the Additional Encryption’ option to apply it. The security feature can be applied to emails sent to anyone, regardless of whether they are within the user’s organisation or even use Gmail. If the recipient does use Gmail, the email will be automatically decrypted in their inbox; if they don’t, they will be sent an invitation to open it in a restricted version of Gmail, which will require them to log in to a guest Google Workspace account. IT teams can request that all external recipients, regardless of whether they use Gmail, must open encrypted emails in the restricted version of Gmail. This may be preferred at hyper security-conscious businesses, as it ensures that communications will not end up stored on third-party servers and devices. IT teams can also retroactively apply security policies or revoke access to emails, in this case. If the recipient has Secure/Multipurpose Internet Mail Extensions (S/MIME) configured — the traditional, resource-intensive protocol for sending encrypted messages that Gmail’s new feature replaces — the email will be sent using it as normal. SEE: Gmail vs Google Workspace: Key Differences for Users & Businesses Gmail’s E2EE doesn’t require extensive IT resources Google can provide end-to-end encryption without requiring businesses to have extensive IT resources, thanks to its cloud storage. The email is encrypted on the sender’s device before being stored in Google’s cloud, eliminating the need for a technical team to acquire and manage certificates. This process makes the message indecipherable to Google and other third parties, ensuring that data protection regulations such as HIPAA are met. In addition, Google is rolling out a number of other security features: An end-to-end encryption default mode for teams handling sensitive data. Classification labels to help users recognise message sensitivity. Data loss prevention tools that enable automatic application of rules to manage and block messages based on their labels. And, a new threat protection AI model has been introduced to enhance Gmail’s defences, using AI to detect spam and phishing attempts before they reach users. How Gmail’s end-to-end encryption democratises high-security emails End-to-end encryption is typically only accessible to regulated companies with large IT budgets. S/MIME requires technical staff to acquire and manage digital certificates — cryptographic keys used to authenticate the sender and encrypt the email — which eats away at their time. Certificates must also be exchanged before the encrypted messages, creating hassle for both the sender and recipient. What’s more, this approach only works if both the sender and recipient have S/MIME implemented, which is only feasible if emails are sent to a small, predefined group of people who are guaranteed to have it set up. There are other options than S/MIME for sending encrypted emails, but they come with their own problems. Encryption features offered by email providers require encryption keys to be shared, creating a security risk. Proprietary point solutions often require the recipient to download a third-party app or extension, which causes inconvenience, and their IT team may not allow it. With Gmail’s end-to-end encryption, only the sender holds the encryption keys, no specialist IT personnel are required, and there’s no need to exchange certificates or use custom software. source

By Nadia Dreid ( March 28, 2025, 6:58 PM EDT) — The Federal Communications Commission has signaled that it’s prepared to be more lenient on deadlines for new licenses after overturning a previous decision that denied a permit to run a newly built FM translator station in Louisiana…. 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 Runway AI Inc. launched its most advanced AI video generation model today, entering the next phase of competition to create tools that could transform film production. The new Gen-4 system introduces character and scene consistency across multiple shots — a capability that has evaded most AI video generators until now. The New York-based startup, backed by Google, Nvidia and Salesforce, is releasing “Gen-4” to all paid subscribers and enterprise customers, with additional features planned for later this week. Users can generate five and ten-second clips at 720p resolution. The release comes just days after OpenAI released a new image generation feature that also allows character consistency across its images. The release created a cultural phenomenon, with millions of users requesting Studio Ghibli-style images through ChatGPT. It was in part the consistency of the Ghibli style across chats that created the furor. The viral trend became so popular that it temporarily crashed OpenAI’s servers, with CEO Sam Altman tweeting that “our GPUs are melting” due to unprecedented demand. The Ghibli-style images also sparked heated debates about copyright, with many questioning whether AI companies can legally mimic distinctive artistic styles. Visual continuity: The missing piece in AI filmmaking until now So if character consistency led to massive viral growth for OpenAI’s image feature, could the same happen for Runway in video? Character and scene consistency — maintaining the same visual elements across multiple shots and angles — has been the Achilles’ heel of AI video generation. When a character’s face subtly changes between cuts or a background element disappears without explanation, the artificial nature of the content becomes immediately apparent to viewers. The challenge stems from how these models work at a fundamental level. Previous AI generators treated each frame as a separate creative task, with only loose connections between them. Imagine asking a room full of artists to each draw one frame of a film without seeing what came before or after — the result would be visually disjointed. Runway’s Gen-4 appears to have tackled this problem by creating what amounts to a persistent memory of visual elements. Once a character, object, or environment is established, the system can render it from different angles while maintaining its core attributes. This isn’t just a technical improvement; it’s the difference between creating interesting visual snippets and telling actual stories. Using visual references, combined with instructions, Gen-4 allows you to create new images and videos with consistent styles, subjects, locations and more. Allowing for continuity and control within your stories. To test the model’s narrative capabilities, we have put together… pic.twitter.com/IYz2BaeW2U — Runway (@runwayml) March 31, 2025 According to Runway’s documentation, Gen-4 allows users to provide reference images of subjects and describe the composition they want, with the AI generating consistent outputs from different angles. The company claims the model can render videos with realistic motion while maintaining subject, object, and style consistency. To showcase the model’s capabilities, Runway released several short films created entirely with Gen-4. One film, “New York is a Zoo,” demonstrates the model’s visual effects by placing realistic animals in cinematic New York settings. Another, titled “The Retrieval,” follows explorers searching for a mysterious flower and was produced in less than a week. From facial animation to world models: Runway’s AI filmmaking evolution Gen-4 builds on Runway’s previous tools. In October, the company released Act-One, a feature that allows filmmakers to capture facial expressions from smartphone video and transfer them to AI-generated characters. The following month, Runway added advanced 3D-like camera controls to its Gen-3 Alpha Turbo model, enabling users to zoom in and out of scenes while preserving character forms. This trajectory reveals Runway’s strategic vision. While competitors focus on creating ever more realistic single images or clips, Runway has been assembling the components of a complete digital production pipeline. The approach feels more akin to how actual filmmakers work — addressing problems of performance, coverage, and visual continuity as interconnected challenges rather than isolated technical hurdles. The evolution from facial animation tools to consistent world models suggests Runway understands that AI-assisted filmmaking needs to follow the logic of traditional production to be truly useful. It’s the difference between creating a tech demo and building tools professionals can actually incorporate into their workflows. AI video’s billion-dollar battle heats up The financial implications are substantial for Runway, which is reportedly raising a new funding round that would value the company at $4 billion. According to financial reports, the startup aims to reach $300 million in annualized revenue this year following the launch of new products and an API for its video-generating models. Runway has pursued Hollywood partnerships, securing a deal with Lionsgate to create a custom AI video generation model based on the studio’s catalog of more than 20,000 titles. The company has also established the Hundred Film Fund, offering filmmakers up to $1 million to produce movies using AI. “We believe that the best stories are yet to be told, but that traditional funding mechanisms often overlook new and emerging visions within the larger industry ecosystem,” Runway explains on its fund’s website. However, the technology raises concerns for film industry professionals. A 2024 study commissioned by the Animation Guild found that 75% of film production companies that have adopted AI have reduced, consolidated, or eliminated jobs. The study projects that more than 100,000 U.S. entertainment jobs will be affected by generative AI by 2026. Copyright questions follow AI’s creative explosion Like other AI companies, Runway faces legal scrutiny over its training data. The company is currently defending itself in a lawsuit brought by artists who allege their copyrighted work was used to train AI models without permission. Runway has cited the fair use doctrine as its defense, though courts have yet to definitively rule on this application of copyright law. The copyright debate intensified last week with OpenAI’s Studio Ghibli feature, which allowed users to generate images in the

A new algorithm has improved the ability of quantum computers to model new materials and chemicals by a factor of 10. That’s according to its developer, UK startup Phasecraft.  The Bristol- and London-based company describes the breakthrough as the largest single leap in quantum simulations to date — moving us a step closer to real-world quantum applications. Quantum computers improve on classical simulations by accurately modelling complex quantum behaviours — like the ever-changing interactions between molecules or the evolution of materials over time — that are too difficult for classical computers to simulate efficiently. This could lead to technological leaps in various fields, from energy to manufacturing and medicine. For example, quantum computers could simulate materials in a battery far more accurately than ever before, enabling scientists to design materials that store energy more efficiently, last longer, and charge faster. The 💜 of EU tech The latest rumblings from the EU tech scene, a story from our wise ol’ founder Boris, and some questionable AI art. It’s free, every week, in your inbox. Sign up now! Currently, quantum computers are not yet fast enough to make those world-changing calculations. Phasecraft’s new algorithm, called THRIFT, promises to accelerate the process. By optimising quantum simulation, THRIFT enables scientists to model new materials and chemicals faster and more accurately, even on today’s slow machines. In tests, THRIFT improved simulation estimates for a key benchmark in quantum physics — the one-dimensional transverse-field Ising model — by a factor of 10. The advance enables simulations that are 10 times larger and can run 10 times longer than those produced by standard methods. The findings were published in Nature Communications today. “We’ve managed to show a 10x increase on today’s machines, and we’d expect this to only get better as the hardware advances and quantum computers become better at tolerating errors and handling more complex calculations,” Raul Santos, Phasecraft’s lead quantum scientist, told TNW. The future of quantum simulations In the last year or so, the obscure world of quantum computing has emerged from the lab and entered the public domain — fuelled by Big Tech’s recent progress in quantum processors. In the past few months alone, Google launched a chip called Willow, Microsoft unveiled Majorana, and Amazon revealed Ocelot.  Advances in quantum computing are only good news for Phasecraft. “This algorithm enhances efficiency on near-term devices, like those Google and Microsoft have announced,” said Santos. “Any improvements in their performance can only enhance our approach.”  Rather than waiting for years or even decades for quantum hardware to mature sufficiently, Phasecraft is redesigning algorithms to work on today’s imperfect quantum machines.   Phasecraft was founded in 2019 by professors Ashley Montanaro (CEO), Toby Cubitt (CTO), and John Morton (director). The company spun out of the University of Bristol and UCL. The startup, which has raised over $20mn to date, works with leading quantum hardware companies, including Google, IBM, and QuEra. source

By Andrew Karpan ( March 28, 2025, 8:07 PM EDT) — A federal judge in Utah has ordered a MasterCard unit to cough up over $2.8 million in legal fees for “aggressively” litigating an “objectively specious” trade secrets suit against two McKinsey consultants who went on to found one of MasterCard’s only serious rivals in a corner of the business analytics software market…. 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 Tom Zanki ( April 1, 2025, 6:20 PM EDT) — Siddhi Acquisition Corp., backed by food and technology-focused private investors, began trading Tuesday after raising an upsized $240 million initial public offering, represented by Loeb & Loeb LLP and underwriters’ counsel Skadden Arps Slate Meagher & Flom LLP…. 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 Bushra Haque and Kara Specht ( March 28, 2025, 5:03 PM EDT) — This article is part of a monthly column that reviews the latest issues facing attorneys practicing before the Patent Trial and Appeal Board. In this installment, we examine the effect of the recent change in discretionary denials…. 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

Today at Forrester’s largest annual customer event in Phoenix, my colleague Barry Vasudevan opened B2B Summit North America with his keynote address, “Introducing Buying Networks: Your Buyers’ New Reality,” which introduced the new concept of buying networks. This wasn’t an easy narrative to deliver, because there are a significant number of challenging and hard-to-stomach realities in B2B today that compel us all to acknowledge that much about how we’ve sold in the past won’t work in the future. This in turn means that revenue enablement teams need to start pivoting — now — or risk irrelevance. Let’s first review some of Barry’s tough-love findings. The Bad News About Buyers Barry told us that “a seemingly never-ending list of people, processes, and technologies involved in making a purchase decision has radically transformed the landscape of business buying.” The hard facts about B2B buyers boil down to the following: Buyers hate buying 81% of buyers are dissatisfied … with the winning provider. Buyers are growing far more complex The average B2B sale now involves 13 internal and 9 external individuals. Buyers are taking longer to buy 86% of purchases experience a significant stall. Buyers are relying on the direct provider less than ever 28% of purchases already include 10+ external influencers. Buyers are using genAI to change everything 89% of buyers are using generative AI agents to support their purchase.   Not very uplifting, is it? But wait, there’s more …  The More Troubling News About Providers Marketing and sales teams within B2B companies remain extraordinarily inward-focused, relying on historically successful or traditional mechanics that fail to address modern realities: Providers focus on revenue growth at the expense of customer goals Only 3% of B2B companies are legitimately customer-obsessed. Providers are losing ground to buyer self-service The self-service technology market size is projected to double by 2032. Providers misalign incentives and behaviors The average conversion ratio from target stage to qualified stage is less than 5%. Providers are not trusted Buyers rank salespeople ninth out of 12 trust options — only ahead of news media, government officials, and social media influencers. Providers rely on archaic processes and metrics B2B CMO dashboards focus on an average of nine organizational value metrics and only two customer value metrics.   All is not lost, however. Barry provided several examples of revenue process transformation success stories, because after all, “big problems require bold solutions.” It starts with graduating the provider organization’s mindset “from checkers to chess.” We must all better respond to the buyer’s needs, their expanding networks, and use of technology with better abilities to collect and interpret signals, maneuver through the buying ecosystem, and acknowledge that outside-in revenue generation approaches override our internal org charts, fiefdoms, and vanity metrics. How Revenue Enablement Can React Today My favorite quote stemming from Barry’s current work is this: “To maximize the lifetime value of the customer, organizations need to maximize lifetime value for the customer,” says Mike Randall, head of global demand generation at Jones Lang LaSalle. Your revenue enablement team can immediately start shifting to a more customer-obsessed mindset by: Cleansing all traditional enablement materials — onboarding curricula, product launch training, methodology reminders — of “What’s in it for me?”-like, “It’s all about us and our products” content. Replace all the self-congratulatory and product-centric enablement references with buyers, personas, markets, business savvy, and whatever else it takes to fulfill Randall’s vision. Reviewing the plans for all upcoming spiffs, SKOs, QBRs, blitz days, and contests to identify recurring mistakes. Are you rewarding seller activity instead of genuine buyer interest? Are you working harder to acquire new logos instead of working smarter to secure renewals? Refining all enablement materials about buyer personas and trends to reflect the realities of their generative AI usage. Sellers can’t and shouldn’t compete with machines but need to be experts on how their buyers are leveraging AI to bypass human interactions … for when they do get in front of their prospect. What Revenue Enablement Must Prepare For Tomorrow Forrester also quotes Ali Rastiello, VP of revenue operations at Health Catalyst: “When my company evaluated offerings from two leading vendors, we chose the provider that demonstrated time after time that they knew who we were and what we wanted to achieve.” This informs my sole, focused recommendation for enablement leaders hoping to support the rise of buying networks: Double down on evolving your seller competencies to adapt to changing buyer needs. Pushing an RDR to make 100 dials per day should give way to hiring, onboarding, and everboarding reps with higher emotional inteligence, a stronger ability to identify and navigate buyer networks, and, above all, an understanding of how to earn customer trust. source