It’s no secret that European tech has a gender equity problem. Men dominate the leadership of most companies in the sector. Women founders struggle to raise VC money, and there’s a stark pay gap between male and female workers. This gender imbalance is especially glaring in the STEM-dominated world of deep tech.  Women lead just 22% of European deep tech companies, according to a new report from the EU-funded GENDEX project, released today. Securing funding remains a challenge, with women-led firms taking six months longer to sign their first term sheet. Over the past decade, women-led companies raised 1.8 times less capital than those led by men. Even those that get funded often face less favourable terms.  European deep tech gender inequity limits diversity of thought and stifles innovation. It’s also pouring hundreds of billions of euros in potential revenue down the drain. Data from the GENDEX report shows that women-led deep tech companies have generated over 11% of the total value raised at non-IPO exits in the past decade — a disproportionately low figure. However, these firms account for just 0.6% of such deals, highlighting the outsized value created when women take the lead. 3 free tickets to TNW Conference? Get them now! For a limited time, groups can get up to three extra free tickets! Book now and increase your visibility and connections at TNW Conference Achieving greater representation of women-led companies at the exit stage — both IPO and non-IPO — over the past decade would have unlocked an estimated €198.8bn in additional value, GENDEX found. “This data proves we need structural change,” said Tanya Suarez, the chair at GENDEX, as well as the CEO of consultancy firm BlueSpecs and founder of tech accelerator IoT Tribe. “Not only is it needed to fairly represent women, but evidence shows a gender-balanced ecosystem delivers the best results.”  Restricting European deep tech talent While women make up 42% of STEM graduates in Europe, their representation drops sharply in the workforce. The GENDEX report finds that women account for just 24% of patent applicants, highlighting a talent drain that limits deep tech’s potential. “Tapping into Europe’s diverse talent pool in the tech and investment sectors in the broadest and most effective way possible is vital if we are to capitalise fully on our many strengths in innovation,” said Stéphane Ouaki, head of department at the European Innovation Council, which funded the report. The deep tech gender imbalance reflects broader societal gender issues. There is no quick fix — addressing it requires systemic change across education, investment, and workplace culture.  However, GENDEX makes four key recommendations to remedy the problem. First, investors should demand that companies report on gender diversity before deploying capital. Second, more funding should be allocated to women-led teams, which have been shown to deliver better outcomes. Third, better legal and funding support is needed for women to secure IP rights. Finally, government co-investment should require gender-balanced portfolios to ensure accountability in public funding. This year’s TNW Conference features a Women in Tech ticket. The pass provides 50% off access to the event, which takes place on June 19-20 in Amsterdam. source

By Al Barbarino ( March 14, 2025, 1:33 PM EDT) — Kenton King helped open Skadden’s Silicon Valley offices some 25 years ago and has lived and breathed tech for a majority of his career, so he’s no stranger to so-called disruptors in the sector. But he said game-changers like artificial intelligence come along only once or twice in a lifetime…. 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

It is no coincidence that the Finnish AI hope Silo AI was bought by the American company AMD. There are few natural exit routes for startups and their investors in Europe other than being sold to the US or listed (preferably in the US). Do you even remember Peltarion, which was the first Swedish “AI company” to get hyped? They were bought by King, the company that makes Candy Crush. That’s a bit of the level we have to work with here. I have met my fair share of enthusiastic entrepreneurs over the years and although many are truly passionate about their product and their companies, I would say that the common thread is that they want to build, grow, and make money. Preferably a lot of money. There is nothing strange about that, but if that development journey is not really offered in the local market, it’s clear that you secure yourself somewhere else, and the US has been the first choice.  For example, look at two Swedes who are reaping success in the US right now, Ali Ghodsi whose Databricks is now valued at over US$62 billion, and Arvid Lunnemark whose Cursor has now reportedly reached a valuation of US$10 billion in a short time. What would have made these gentlemen stay and build their successful companies in Europe instead? Would it have been impossible? source

By Hailey Konnath ( March 13, 2025, 11:37 PM EDT) — The Ninth Circuit has rejected Uber Technologies Inc.’s contention that the Judicial Panel on Multidistrict Litigation should’ve enforced Uber’s “non-consolidation” clause with passengers’ lawsuit alleging they were sexualy assaulted, ruling that such a “private agreement” doesn’t override the JPML’s power to consolidate…. 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

One of our 2025 banking predictions was that banking customer experience (CX) would continue to decline, on average, across the globe. And indeed, the year hasn’t started well, after IT outages left the customers of UK’s largest banks, Barclays and Lloyds, unable to access their money or make payments. This is similar to what happened at Bank of America last October. Dependability is one of the key levers of banking trust, but of course, IT resilience and availability is not something that CX professionals control. There are many other things, however, that they can do to improve customer experience and loyalty. To help banking executives identify what those things are, we’ve interviewed the top scorers in Forrester’s Customer Experience Index (CX Index™) to identify some best practices. Our two newly published reports highlight best practices from across both frontstage and backstage. So what are some of our key findings? Focus On Creating Customer Value — Not Just Fixing Broken Experiences There’s a number of reasons for the drop in CX quality, but chief among them is the poor performance of banks on emotion — which influences customer loyalty more than ease or effectiveness. The top emotions that drive loyalty in certain regions include feeling confident, valued, and respected. Yet most CX teams are too tactical to shift the dial on emotion, opting instead to monitor customer feedback to identify broken experiences rather than tackling big challenges, such as the lack of customer-obsessed culture, opaque products or customer communications, or complex cross-channel journeys. The shift of customers to digital channels, while convenient and cost-effective, is also failing to elicit a deep emotional connection between banks and their customers. CX banking leaders look for opportunities to create new highs and connect with customers emotionally. According to Caroline Tucker, VP of CX transformation at Navy Federal Credit Union, “It’s not just about improving interactions. It’s about creating new interactions that don’t exist today to delight our members […] The art is thinking through the emotional arcs along that journey and inserting interactions that could be a nice delighter and make a lasting impression.” This requires blending methodologies to drive divergent and convergent thinking. Hire Exceptional People — And Keep Training Them As banks look to reduce the cost to serve and continue to boost digital self-service chatbot capabilities, it’s easy to forget that exceptional people are often behind exceptional experiences. Leading banks hire people with the right attitude, train them, and empower them to do what’s right for the customer. This applies particularly to customer-facing employees but not only. For example, UK-based first direct focuses on recruiting exceptional people who aren’t necessarily bankers but who demonstrate empathy, kindness, and the willingness to go the extra mile. The bank invests significantly in training, focusing on developing skills related to connecting with the customer, listening, and creating trust. In the words of Lucinda Scott, customer service director at first direct: “You do not need a bank when things are good. We train our customer service agents to solve problems. The agent and the team leader listen to the call together to reflect on what went well and how they can go the extra mile. Were they listening to catch the true customer need? For example, if the customer doesn’t say they’re struggling, the agent must have the skills to identify vulnerable customers who are going through a difficult time.” For other best practices, Forrester clients can read the frontstage and backstage reports or connect with me via inquiry or guidance session. We will also discuss these and other topics at our upcoming CX Summit EMEA this year, so please join us June 2–4 in London. source

By Bryan Koenig ( March 14, 2025, 2:01 PM EDT) — Marketing communications giants Omnicom and Interpublic disclosed an in-depth Federal Trade Commission probe into their $13 billion merger, pumping the brakes on their ability to close the deal soon, but they said the expectation is nevertheless to finish by the second half of this year…. 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 Nous Research, the New York-based AI collective known for developing what it calls “personalized, unrestricted” language models, has launched a new Inference API that makes its models more accessible to developers and researchers through a programmatic interface. The API launch represents a significant expansion of Nous Research’s offerings, which have gained attention because they challenge the more restricted approaches of larger AI companies like OpenAI and Anthropic. “We heard your feedback, and built a simple system to make our language models more accessible to developers and researchers everywhere,” the company announced on social media. The initial API release features two of the company’s flagship models: Hermes 3 Llama 70B, a powerful general-purpose model based on Meta’s Llama 3.1 architecture, and DeepHermes-3 8B Preview, the company’s recently released reasoning model that allows users to toggle between standard responses and detailed chains-of-thought (CoT). Today we’re releasing our Inference API that serves Nous Research models. We heard your feedback, and built a simple system to make our language models more accessible to developers and researchers everywhere. The initial release features two models – Hermes 3 Llama 70B and… pic.twitter.com/dAEA8donln — Nous Research (@NousResearch) March 12, 2025 Inside Nous Research’s waitlist-based portal: How the AI upstart is managing high demand To manage demand, Nous has implemented a waitlist system through its new portal, with access granted on a first-come, first-serve basis. The company is providing all new accounts with $5 in free credits. Developers can access the API documentation to learn more about integration options. The waitlist approach provides critical insight into Nous Research’s strategic positioning. Unlike major players with massive GPU reserves, Nous faces the infrastructure constraints common to smaller organizations in AI. The waitlist serves as both a technical necessity and a marketing tactic, creating an exclusivity that generates buzz while managing computational load. What makes this approach particularly notable is how it reflects Nous’s grassroots ethos. While the company positions itself as an alternative to big tech AI, it’s also adopting pragmatic business strategies that acknowledge the realities of scaling inference services. This tension between idealism and practicality will likely define Nous’ journey as it transitions from purely open-source releases to commercial offerings. The API follows OpenAI’s API design pattern for completions and chat completions, making it potentially easier for developers already familiar with that interface to integrate Nous’ models into their applications. From GitHub downloads to cloud API: Nous Research’s evolution signals a new business model This API launch comes just four months after Nous debuted Nous Chat, the company’s first user-facing chatbot interface. While the company has released numerous open-source models for local deployment, the new API allows developers to access high-performance versions of these models without managing their own infrastructure. “Previously, if researchers and users wanted to actually deploy these models, they needed to download and run the code on their own machines — a time-consuming, finicky and potentially costly endeavor,” VentureBeat executive editor Carl Franzen wrote in his coverage of the Nous Chat launch. DeepHermes-3, released just last month, represents the company’s entry into the increasingly competitive field of reasoning-focused AI models. The model allows users to switch between concise responses and detailed reasoning processes through a system prompt that activates its “thinking” capabilities. The ‘unrestricted AI’ philosophy: How Nous Research challenges big tech’s guardrails Since its founding in 2023, Nous Research has positioned itself as an alternative to more tightly controlled AI systems. The company emphasizes individual agency and alignment with user needs, reflected in blog posts with titles like “Freedom at the frontier” and “From black box to glass house: The imperative for transparent AI development.“ “Superintelligence should solve for maximal individual agency and freedom of spirit,” the company wrote in a recent blog post announcing its Psyche project on Solana. “Its development cannot be left solely in the hands of a few corporations and oligarchs.” This philosophical stance has resonated with developers seeking more flexible AI systems, although the approach has also raised questions about responsible deployment. Despite marketing itself as “unrestricted,” the company’s models do include some guardrails against harmful outputs. Monetizing open AI research: Nous’s API strategy and roadmap for Hermes, DeepHermes and beyond The API launch signals Nous Research’s move toward a more sustainable business model while maintaining its commitment to open source principles. According to the company’s release timeline, Nous has released 29 AI artifacts since July 2023, including models, papers, code and datasets. The API represents a delicate but crucial evolution in Nous Research’s business model. By commercializing deployment while continuing to release model weights, Nous is attempting to square a difficult circle: Generating revenue without alienating the open-source community that forms its foundation. This hybrid approach appears designed to capture different segments of the market. Individual developers and researchers can still download and run models locally, while enterprises seeking reliability, convenience and performance optimization can pay for API access. In effect, Nous is monetizing the infrastructure and optimization layer rather than the models themselves — a strategy that addresses the fundamental economic challenge of open-source AI without compromising its core principles. The success of this approach may determine whether independent AI labs can establish sustainable business models that preserve their independence from big tech or venture capital firms that might push for more aggressive commercialization. For developers concerned about AI centralization, Nous’ experiment represents a potential middle path that could maintain diversity in the AI ecosystem. Nous Research indicates that its inference offerings will expand over time, potentially including more of its models like Hermes 2 Pro, which specializes in function-calling, or its Psyche project. For the growing ecosystem of AI startups building on open models, the new API provides another option beyond established players like Together AI, Anthropic and OpenAI, potentially increasing competition and driving further innovation in the AI inference space. “We welcome your ideas to help shape the future,” the company noted in its announcement,

Gone are the days of the leather wallet and chunky billfold. Instead, people are turning to digital wallets: mobile phone-, tablet- and smartwatch-based tools that securely store payment details and other information. This technology is used to make payments in a more secure fashion than traditional credit card swipes and cash. But there are other benefits too, especially for small business owners. Let’s dive into what digital wallets are, how they work, and how they’re going to help your business up its payments game. What is a digital wallet? A digital wallet is a virtual tool that allows businesses and individuals to store and manage payment information electronically through a secure app that encrypts payment info. This safekeeping eliminates the need to carry physical bank cards. Anytime you need to pay someone, you simply tap your smartphone or device and the digital wallet handles the rest. These apps are all the rage. Capital One’s 2025 Digital Wallet Statistics research report found that as early as 2023, 53% of American shoppers relied on a digital wallet more than a traditional version. Worldwide, there are over 3.4 billion digital wallets in existence, which will swell to over 5 billion by 2026. The benefits are mutual for consumers and small business owners. Digital wallets speed up transactions thanks to simplified checkout. They also avoid cumbersome cash transactions and reduce the risk of handling physical cards. These improvements can spawn increased revenue and happier customers. It’s not all about the money, though. Digital wallets can also keep frequent flier points, loyalty cards, coupons, tickets, and personal identification documents close at hand. SEE: What is a Cashless Society? How do digital wallets work? Digital wallets function by securely storing users’ payment information. A person must first create a wallet, and then enable it on their smartphone using an app. Apple Pay and Google Pay are two examples of popular digital wallets. Once an account is created, they add their payment source details to the platform by either entering the information or using the phone’s camera to scan all the relevant data straight into the app. When a person makes a purchase, the wallet charges a person’s bank card or other source of funds. However, the merchant isn’t privy to private data. Instead, the wallet sends the money to the business, cloaking actual account numbers. This eye for security protects everyone involved and makes it hard for fraudsters to lift credit card numbers. In-person payments via a digital wallet rely on near-field communication (NFC) to enable touchless transactions. For example, a customer can tap their smartphone to an NFC-enabled terminal to complete a purchase. Some wallets also generate one-time codes or use QR codes for added security. Did you know? Digital wallets can also be used to pay for online purchases. Customers will just have to choose their digital wallet from the checkout options and either enter the transaction reference or scan a QR code displayed on the screen to complete the payment. Some are even more sophisticated and can be accessed outside of the app. For example, PayPal users can log on to their PayPal wallet from a web browser. Digital wallets typically support multiple funding sources, such as credit and debit cards, cryptocurrency, and bank accounts. These options grant users flexibility over how they pay. For example, if a customer forgets their billfold at home, they can still pull up their preferred credit card on their smartphone. SEE: What is a Digital Payment? Types of digital wallets Let’s go over the three main types of digital wallets. Closed wallets Closed wallets are specific to a particular company or brand. They allow customers to make transactions only with the issuer of the wallet. For example, Amazon Pay is a closed wallet that enables customers to store funds and perform transactions primarily within the Amazon ecosystem. There is limited use outside this realm. Small businesses yearning to exact control over their customers’ transactions may offer closed wallets. Semi-closed wallets Semi-closed wallets enable users to transact with a select group of merchants accepting the wallet. An example is Paytm, which allows customers to pay online and offline merchants, provided they are authorized. This type of wallet is ideal for businesses operating within a specific network of partners. Open wallets Open wallets are the most versatile. They allow users to make payments across various platforms and stores, both online and in physical locations. Examples include Apple Pay, Google Wallet, and PayPal. This type is more conducive to small businesses because they reach a broader range of customers. SEE: Top 6 Mobile Payment Methods to Consider Pros and cons of digital wallet payments Pros Convenience: Digital wallets eliminate the need to carry physical cards and remember PINs, making it more convenient for consumers. Easy to use: With the prevalence of smartphones and mobile apps, customers easily learn how to use digital wallets in their day to day transactions. Increased security: Encryption and one-time codes are used to secure transactions. Some providers support biometric verification like facial recognition. Contactless payments: A simple tap of the device or QR code scan is all that’s needed to transact, making it a breeze at checkout. Integrated loyalty programs: Many digital wallets house rewards programs, like frequent shopper points and virtual punchcards — which is a boon for small businesses trying to boost loyalty. Reduced costs: Enhanced security and faster checkout times are conducive to more satisfied customers and a better bottom line. Cons Limited adoption: The tried-and-true swipe or cash transactions are still commonplace, but digital payments are growing by leaps and bounds. Dependence on technology: If the internet or cellular network coverage is spotty, some digital wallets won’t work. And, of course, a dead phone battery could mean the transaction itself is DOA. Startup costs: You’ll need to purchase NFC-enabled payment terminals or a QR code reader. You may also pay increased fees to accept some forms of payment common to digital wallets, like cryptocurrency. Security risks: Though digital wallets are

Market shifts, evolving customer behaviors, and regulatory changes can turn a once-powerful AI tool into a liability, Pallath says. Left unchecked, AI might produce outdated or even harmful results, eroding trust, revenue, and competitive edge, he says. “Build dedicated teams to monitor AI performance, automate updates, and refine models continuously,” Pallath says. “Treat AI as a living system — one that thrives on iteration, learning, and proactive governance to deliver sustained value. Success isn’t just about deployment — it’s about long-term commitment to excellence.” Ignoring responsible AI frameworks One of the most dangerous oversights in AI implementation is neglecting to establish robust ethical frameworks, Pallath says. “Without clear guidelines for responsible AI use, organizations risk deploying biased algorithms, mishandling sensitive data, or pursuing problematic use cases that can trigger regulatory penalties and reputation damage,” he says. source