German startup FibreCoat has bagged €20mn in Series B funding as it looks to bring its super-resistant materials to the burgeoning space industry.  FibreCoat spunout from RWTH Aachen University in 2020. The startup has developed a patented process for coating fibres with metals and plastics during the spinning stage. This creates fibres that are lightweight and conductive, yet strong and durable — at a fraction of conventional costs. These can then be spun together to form reinforced composites.  So far, FibreCoat has focused on securing clients in the automotive, construction, and defence industries, where the materials are particularly useful for radiation shielding and weight reduction applications. Now the company is setting its sights on upward. Spacecraft require materials that can withstand extreme temperatures, radiation, and electromagnetic interference (EMI) without adding unnecessary weight. “Space is a rapidly growing sector, and launchers and satellites increasingly need coated fibres to endure harsh conditions,” said Dr. Robert Brull, CEO of FibreCoat.  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! Luxembourg-based NewSpace Capital co-led the funding round, bringing vital expertise as the startup looks to cash in on the expanding space ecosystem, projected to reach $1.8trn by 2035.  “Space and terrestrial supply chains are converging,” said Bogdan Gogulan, managing partner at NewSpace Capital, adding that FibreCoat has the potential to address critical challenges across a swathe of industries. FibreCoat will use the fresh funds to ramp up R&D and scale production as it looks to commercialise its fibre coating technology.  The startup is far from the only spinout access story to emerge from RWTH Aachen in recent years.    One of the fastest growing is Cylib. The startup is currently constructing what is set to be Europe’s largest EV battery recycling plant.  Cylib’s founders — Dr Lilian Schwich, Paul Sabarny, and Dr Gideon Schwich — launched the company after a decade of battery recycling research at RWTH Aachen. The partners claim their method uses 30% less energy than competitors.  Another big player is Black Semiconductor, which raised €254.4mn back in June. That’s a massive raise for any startup, let alone a European one. Even more impressive is that the company is only four years old.  Brothers Daniel and Sebastian Schall launched Black Semiconductor in 2020. The startup is developing a new type of chip-connecting technology using the “wonder material” graphene. source

Open-source software is a lifesaver for startups and enterprises alike as they attempt to deliver value to customers faster. While open source use isn’t considered dubious for business use like it once was, the very open nature of it leaves it open to poisoning by bad actors.   “Open-source AI and software can present serious national security risks — particularly as critical infrastructure increasingly relies on them. While open-source technology fosters rapid innovation, it doesn’t inherently have more vulnerabilities than closed-source software,” says Christopher Robinson, chief security architect at the Open Source Security Foundation (OpenSSF). “The difference is open-source vulnerabilities are publicly disclosed, while closed-source software may not always reveal its security defects.”  Incidents such as XZ-Utils backdoor earlier this year demonstrate how sophisticated actors, including nation-states, can target overextended maintainers to introduce malicious code. However, the XZ-Utils backdoor was stopped because the open-source community’s transparency allowed a member to identify the malicious behavior.  “At the root of these risks are poor software development practices, a lack of secure development training, limited resources, and insufficient access to security tools, such as scanners or secure build infrastructure. Also, the lack of rigorous vetting and due diligence by software consumers exacerbates the risk,” says Robinson. “The threats are not limited to open source but extend to closed-source software and hardware, pointing to a broader, systemic issue across the tech ecosystem. To prevent exploitation on a national level, trust in open-source tools must be reinforced by strong security measures.”  Related:Let’s Revisit Quality Assurance Open Source: Get What You Paid For?  A primary threat is the lack of support and funding for open-source maintainers, many of whom are unpaid volunteers. Organizations often adopt open-source software without vetting security, assuming volunteers will manage it.   Another often overlooked issue is conflating trust with security. Simply being a trusted maintainer doesn’t ensure a project’s security. Lawmakers and executives need to recognize that securing open source demands structured, ongoing support.  “AI systems, whether open or closed source, are susceptible to prompt injection and model training tampering. OWASP’s recent top 10 AI threats list highlights these threats, underscoring the need for robust security practices in AI development. Since AI development is software development, it can benefit from appropriate security engineering,” says Robinson. OWASP is the Open Worldwide Application Security Project.  “Without these practices, AI systems become highly susceptible to serious threats. Recognizing and addressing these vulnerabilities is essential to a secure open-source ecosystem.”  Related:Soft Skills, Hard Code: The New Formula for Coding in the AI Era At the company level, boards and executives need to understand that using open-source software involves effective due diligence and monitoring and contributing back to its maintenance. This includes adopting practices like creating and sharing software bills of materials (SBOMs) and providing resources to support maintainers. Fellowship programs can also provide sustainable support by involving students or early-career professionals in maintaining essential projects. These steps will create a more resilient open-source ecosystem, benefiting national security.  “Mitigating threats to open source requires a multifaceted approach that includes proactive security practices, automated tools, and industry collaboration and support. Tools like OpenSSF’s Scorecard, GUAC, OSV, OpenVEX, Protobom, and gittuf can help identify vulnerabilities early by assessing dependencies and project security,” says Robinson. “Integrating these tools into development pipelines ensures that high-risk issues are identified, prioritized and addressed promptly. Additionally, addressing sophisticated threats from nation-states and other malicious actors requires collaboration and information-sharing across industries and government.”  Related:Develop an Effective Strategy for User Self-Help Portals Sharing threat intelligence and establishing national-level protocols will keep maintainers informed about emerging risks and better prepared for attacks. By supporting maintainers with the right resources and fostering a collaborative intelligence network, the open-source ecosystem can become more resilient.  Infrastructure Is at Risk  While the widespread use of open-source components accelerates development and reduces costs, it can expose critical infrastructure to vulnerabilities.   “Open-source software is often more susceptible to exploitation than proprietary code, with research showing it accounts for 95% of all security risks in applications. Malicious actors can inject flaws or backdoors into open-source packages, and poorly maintained components may remain unpatched for extended periods, heightening the potential for cyberattacks,” says Nick Mistry, CISO at software supply chain security management company Lineaje. “As open-source software becomes deeply embedded in both government and private-sector systems, the attack surface grows, posing a real threat to national security.”  To mitigate these risks, lawmakers and C-suite executives must prioritize the security of open-source components through stricter governance, transparent supply chains and continuous monitoring.   Dependencies Are a Problem  Open-source AI and software carry unique security considerations, particularly given the scale and interconnected nature of AI models and open-source contributions.  “The open-source supply chain presents a unique security challenge. On one hand, the fact that more people are looking at the code can make it more secure, but on the other hand, anyone can contribute, creating new risks,” says Matt Barker, VP & global head, workload identity architecture at machine identity security company Venafi, a CyberArk Company. “This requires a different way of thinking about security, where the very openness that drives innovation also increases potential vulnerabilities if we’re not vigilant about assessing and securing each component. However, it’s also essential to recognize that open source has consistently driven innovation and resilience across industries.”  Organizational leaders must prioritize rigorous evaluation of open-source components and ensure safeguards are in place to track, verify, and secure these contributions.   “Many may be underestimating the implications of mingling data, models, and code within open-source AI definitions. Traditionally, open source is applied to software code alone, but AI relies on various complex elements like training data, weights and biases, which don’t fit cleanly into the traditional open-source model,” says Barker. “By not distinguishing between these layers, organizations may unknowingly expose sensitive data or models to risk. Additionally, reliance on open source for core infrastructure without robust verification procedures or contingencies can leave organizations vulnerable to cascading issues if an open-source component is compromised.”  Thus far, the US federal government has not imposed limits

This short guide covers how to use a traditional fax machine and a few troubleshooting tips if your fax isn’t sending. I’m also going to cover a few online faxing options that don’t require a fax machine, a multifunction printer, or even a phone line. You don’t need anything but an internet connection in order to send a fax from your iPhone, Android, or computer. 1 RingCentral RingEx Employees per Company Size Micro (0-49), Small (50-249), Medium (250-999), Large (1,000-4,999), Enterprise (5,000+) Medium (250-999 Employees), Large (1,000-4,999 Employees), Enterprise (5,000+ Employees) Medium, Large, Enterprise Features Hosted PBX, Managed PBX, Remote User Ability, and more How to use a fax machine When we say fax machine, we’re referring to the standalone piece of hardware that scans and transmits physical pages with a document feeder tray and a connection to a phone line. Below are the steps you need to take to send a traditional fax. Step 1: Check the power and connection Press the power button and wait for the control panel to light up. Once this happens, you know the machine is ready to use. If the fax machine is not used often, confirm that the phone line cable coming from the fax machine is securely plugged into the wall socket. Step 2: Add a fax cover sheet It’s a good practice to include a cover sheet for the document you’re faxing, especially if you’re sending it to a business where multiple people use the same machine. This is by no means required, but it helps ensure the fax gets to the right person. Certain organizations may require a fax cover sheet, so keep an eye out for those to ensure that there are no unnecessary delays. A cover sheet typically includes the following information: Your company name. Your contact information. The recipient’s name and fax number. The total number of pages. The send date. Once your cover sheet is ready, place it on top of the first page of the document you’re sending. The pages should be arranged in front-to-back order, starting with the cover sheet. Here are a few fax cover sheet templates you can use to stay organized. Step 3: Put the document into the fax machine Look at the feeder tray to determine whether you need to place the document face up or face down. Once you determine the direction your document should face, place it into the feeder tray. Include all of the pages you need to send, collated in the correct order from first to last. Tip: If you need to fax a check or document that is not the right size for the feeder tray, make a photocopy of it first. Step 4: Input the destination number Use the keypad to dial the number for the fax machine you’re sending the document to. Be sure to input the full number, including the area code and country code, if necessary. Also, if your business requires a code to dial out, you’ll need to include this before anything else. An example fax number sent from a machine that requires a code to dial out might look like this: 9-225-555-9876. Step 5: Press send Press the Send or Start button. Prepare yourself for an onslaught of beeps, buzzes, and general screeching sounds. The noise can be alarming, but it means it’s working. Wait for all of the pages you’re sending to go through the feeder. Step 6: Confirm the fax was sent Once all the pages have been sent, the fax machine will print out a transmission report. The details included in the report vary between machines, but generally, it will have the following: Date and time: When the fax was sent. Transmission status: Indicates whether the fax was successfully sent or if it failed. Page count: The number of pages sent. Destination number: The fax number to which the document was sent. Error codes: If the transmission fails, error codes may be displayed to help diagnose the issue. Duration: How long the transmission took. If the transmission report confirms that the fax was sent successfully, you’re all done! If the fax failed, move on to the troubleshooting section below. Fax troubleshooting tips Fax can be frustrating, I know, but there are a few simple fixes that can help: Check the connection: Ensure that the phone cable is securely connected and that there’s a dial tone. A good connection is the first step to successful faxing. Turn it off and on again: This is classic IT advice for a reason — it usually works. Avoid paper jams: Make sure none of your pages are stuck in the feeder. If one gets jammed, gently remove it, straighten the paper out, and try again. Keep in mind that you’ll probably need to resend the whole document, not just the page that was jammed. Check for error messages: Most transmission reports include information about why the fax failed, such as error codes. Look up the error codes in your fax machine’s manual and follow the directions to fix it. If you don’t have the manual or the instructions are confusing, call customer service for help. If you are still having issues, check out this full-length post I wrote about what to do when a fax won’t go through. Do I need a phone line to use a fax machine? No, you don’t need a phone line to use a fax machine. With the help of a fax analog telephone adapter (ATA), you can keep your same old fax machine or multifunction printer to send faxes over the internet instead of a phone line. Here’s how you do it: Purchase an ATA. It will come with the ATA device, a power adapter, an Ethernet cable, and a standard phone cable. Connect one end of a phone cable to your fax machine and the other to the Phone 1 port on the ATA. Connect one end of your Ethernet cable to the Internet port on the ATA, and the other

COMMENTARY As a child, airplanes fascinated me — I was taken by their gravity-defying magic, their technical wonders, their sleek designs, and the adventures they unlocked. I dreamed of flying one myself. Although I pursued a career in cybersecurity, flying always inspired me — so I chased my lifelong dream of becoming a licensed pilot. I continue to fly light aircraft in the little spare time I get alongside my role as the CEO of a leading cyber-risk management company.  Always Have Backup A recent experience prompted me to think more closely about the interplay between my two passions.  Not long ago, I completed an advanced course for pilots of two-engine planes. Previously, I had only flown planes with one engine, which is a risk: If the engine malfunctions, you’re in big trouble.  In the final training session, we practiced different responses in the event of an engine breaking down. As our instructor walked us through different tactics, one thought went through my mind: the critical need for a “defense in depth” approach to security. Just as the smooth functioning of an airplane relies on multiple mechanisms supporting one another, a modern cybersecurity platform also leverages numerous defensive techniques, so that if a threat slips through one layer, it will be caught by another.  That was when I realized: While aviation and cybersecurity may appear as far apart as the heavens and earth, the skills I’ve learned from flying have profoundly influenced my career.   Know Your Environment Even at the beginning of my career, as a junior systems analyst and IT team manager, I understood that an organization’s cybersecurity posture is much broader than any single tool or platform. Effective cybersecurity requires a thorough understanding of the operating environment and all the tools therein. Before an organization can identify vulnerabilities and secure itself against attacks, it needs a complete understanding of its internal and external assets, digital surfaces, devices, brand assets, and more.  Likewise, becoming a pilot not only required me to master the practical skills of navigating an aircraft through various conditions but also necessitated a deep understanding of the equipment on board. Flying without a confident grasp of my instruments or expected flight environment is like playing Russian roulette: potentially fine … or lethal.  In cybersecurity, just as in aviation, one can never be passive. Full visibility into a technology environment is required to be able to manage risks, quickly adjust course, identify and communicate issues, and fix those issues under pressure.  Continuous Learning and Testing In the modern cybersecurity landscape, threats are always evolving, and hackers are constantly honing their skills. That’s why I ensure my company continuously tests its defenses and my employees constantly learn new skills to keep pace with the rapidly changing threat landscape.  During a recent performance review with one of my direct reports, the employee suggested that some of our threat simulations and training sessions were so time-consuming that they prevented his team from carrying out other deliverables. I acknowledged that learning and testing take up a lot of time, but doubled down on the importance of learning from past incidents to understand future threats and tactics. A cybersecurity company that prioritizes this will serve its customers better in the long run, even if it means a routine report or product update will be slightly delayed.  Muscle Memory and Task Execution A little-known insight into a pilot’s mindset: When landing my aircraft, I barely think about what I am doing. That’s because I have practiced and repeated the same maneuver hundreds of times, making complex tasks feel like second nature.  It’s just as vital to develop this sort of muscle memory among security professionals. Security teams should regularly practice routine protocols for any scenario. Conducting tabletop exercises and attack simulation drills allows teams to react quickly and effectively when a real threat emerges.  By promoting constant preparedness, I aim to ensure that my teams can execute the best course of action without hesitation, even in high-pressure situations. Small Issues Become Big Ones After flying for a few years, I felt like I’d finally memorized the dozens of separate tasks that form part of a pre-flight checklist. In reality, I’d started to prioritize — I knew that I’d always have to check whether there was enough fuel in the tank to complete the journey, but making sure each seatbelt on the plane was fastened correctly seemed secondary.  One time, I experienced a particularly bumpy landing. I asked a fellow pilot why that might have occurred, and he suggested checking the air pressure in the tires. I took a look and realized that I’d completely forgotten to check the tires before the flight. A tire low on air won’t cause the plane to fall from the sky, but landing on a flat tire can be extremely dangerous. If a flat tire hits the runway, it could burst and send the plane swerving. Incidents like this can easily be avoided — by running through the correct procedures to identify any small issue before it becomes a big one.  In cybersecurity, small vulnerabilities in a system can easily be overlooked and are therefore ripe for exploitation. In short, cybersecurity is not just about responding to attacks — it’s about mitigating risks before they can cause damage. By implementing best practices and checklist procedures, security teams can do just that.   The Sky’s the Limit The lessons I’ve learned soaring through the skies have extended far beyond the runway.  Learning from my mistakes and internalizing the discipline it takes to be a pilot have allowed me not only to lead my company with clarity and resilience; it also has provided me with a new perspective on the ever-evolving landscape of cybersecurity. Incorporating these lessons into the flight plan of my professional life has helped foster a culture of continuous improvement at our workplace, which ultimately has helped our customers.  source

“The likelihood of your largest enterprise customers being harmed is minimal,” Kimball said. “If there is a victim in this, it’s the small businesses. They are the ones who are being impacted.” Jim Mercer, the program VP for software development at IDC, said the lawsuit’s accusations are nothing new for the fiercely competitive cloud space.  “The competition among the big hyperscalers — major cloud service providers like Amazon Web Services (AWS), Microsoft Azure, and Google Cloud — is intense due to the high stakes in dominating the cloud computing market,” Mercer said. “These companies are competing on multiple fronts, including pricing, innovation, scalability, infrastructure, performance, and service offerings, such as genAI capabilities. The hyperscalers are using whatever strengths or leverage they have to win market share.” source

A police force in the UK is using Bluetooth tracking wristbands for people with dementia in a high-tech bid to keep them safe.   Starting this month, Avon and Somerset Police will start giving out Bluetooth wristbands for free to families. It’s part of a broader initiative to protect dementia patients, who often suffer from extreme memory loss and confusion as a result of the incurable condition. The wristbands are fitted with Tile, a popular tracking device similar to the Apple Airtag. Once the tag is attached to a patient, caregivers can track their location via a smartphone app. If the person strays too far, the app sends out an alert.   The Tile tags’ Bluetooth range is typically limited to a few hundred metres. However, the device can make a virtual “handshake” with other smartphones running the Tile app, to create a crowdsourced tracking network. Life360, the US firm that makes Tile, claims over 76 million people use its app globally.   Webinar: Unicorn DNA: The Blueprint for Scaling Success What does it take to build a unicorn? Top executives of unicorn companies reveal the mindset, strategies, and innovative thinking that propelled their companies to the top. Dementia is a growing problem globally, with over 55 million people currently living with the condition, according to the World Health Organisation.  The scheme was launched by Inspector Stuart King in 2015, following a rise in missing person incidents involving people living with dementia.     “The introduction of Bluetooth-enabled devices from Life360 and Tile is a significant step forward in safeguarding those living with dementia,” said Inspector King.  “These discreet and user-friendly devices not only offer reassurance to families but can be a critical tool in emergencies, enabling quick response and timely assistance,” he said.   Tile also incorporates QR code functionality. When the QR code on the back of the device is scanned, it allows the next of kin or carer to be contacted directly via phone or text.   Unlike GPS devices which need regular charging, the battery on the Bluetooth wristbands should last for about three years. The initiative comes amid a boom in health tech, as startups develop high-tech solutions everything from machines that help detect cancer to algorithms that fastrack the discovery of new drugs.  source

The end of each year brings a swarm of predictions, prognostications, and tea leaf readings on what technology is expected to take off in the year to come. While there is no doubt technology will continue to evolve and transform the enterprise world, not every forecast will hold water, and some might even distract organizations from relevant developments. Rather than pore over predictions for 2025, DOS Won’t Hunt gathered a panel to discuss what actually mattered to companies in 2024 versus the expectations that started the year. This episode brought together Rocky Cole, co-founder and COO of iVerify; Bogdan Raduta, head of AI with FlowX.AI; Bryan Wood, machine learning solutions engineer at Snorkel AI; Dave Merkel, CEO and co-founder of Expel; Alvaro Oliveira, chief talent officer with Andela; and John Peluso, chief technology officer at AvePoint. How did predictions on technology talent and the workforce play out in 2024? Did anything develop in the AI world that met or exceeded predictions? Did cybersecurity get struck with unexpected developments? Were there any surprises in technology that eclipsed predictions? Listen to the full podcast here. source

Large language models (LLMs) just keep getting better. In just about two years since OpenAI jolted the news cycle with the introduction of ChatGPT, we’ve already seen the launch and subsequent upgrades of dozens of competing models. From Llama3.1 to Gemini to Claude3.5 to GPT-o1, the list keeps growing, along with a legion of new tools and platforms used for developing and customizing these models for specific use cases. In addition, we’ve seen the introduction of a wide variety of small language models (SLMs), industry-specific LLMs, and, most recently, agentic AI models. The sheer number of options and configurations, not to mention the costs associated with these underlying technologies, is multiplying so quickly that it’s creating some very real challenges for businesses that have been investing heavily to incorporate AI-powered capabilities into their workflows.     In fact, business spending on AI rose to $13.8 billion this year, up some 500% from last year as companies in every industry are shifting from experimentation to execution and embedding AI at the core of their business strategies. For companies that want to keep pace with each new advancement in a world that’s moving this fast, simply buying the latest, greatest, most powerful LLM will not address their needs. Computing costs rising Raw technology acquisition costs are just a small part of the equation as businesses move from proof of concept to enterprise AI integration. As many companies that have already adopted off-the-shelf GenAI models have found, getting these generic LLMs to work for highly specialized workflows requires a great deal of customization and integration of company-specific data. Applying customization techniques like prompt engineering, retrieval augmented generation (RAG), and fine-tuning to LLMs involves massive data processing and engineering costs that can quickly spiral out of control depending on the level of specialization needed for a specific task. In 2023 alone, Gartner found companies that deployed AI spent between $300,000 and $2.9 million on inference, grounding, and data integration for just proof-of-concept AI projects. Those numbers are only growing as AI implementations get larger and more complex. The rise of vertical AI To address that issue, many enterprise AI applications have started to incorporate vertical AI models. These domain-specific LLMs, which are more focused, and tailor-made for specific industries and use cases, are helping to improve the level of precision and detail needed for certain specialized business functions. Spending on vertical AI has increased 12x, this year, as more businesses recognize the improvements in data processing costs and accuracy that can be achieved with specialized LLMs. At EXL, we recently launched a specialized Insurance Large Language Model (LLM) leveraging NVIDIA AI Enterprise to handle the nuances of insurance claims in the automobile, bodily injury, workers’ compensation, and general liability segments. Our LLM was built on EXL’s 25 years of experience in the insurance industry and was trained on more than a decade of proprietary claims-related data. We developed the model to address the challenges many of our insurance customers were having trying to leverage off-the-shelf LLMs for highly specialized use cases. Because those foundational LLMs do not include private insurance data or a domain-specific understanding of insurance business processes, our clients found they were spending too much time and money trying to customize them. Our EXL Insurance LLM is consistently achieving a 30% improvement in accuracy on insurance-related tasks over the top pre-trained models, such as GPT4, Claude, and Gemini. As a result, our clients are seeing enhanced productivity and faster claim resolution with lower indemnity costs and claims leakage – all-powerful value drivers. Choreographing data, AI, and enterprise workflows While vertical AI solves for the accuracy, speed, and cost-related challenges associated with large-scale GenAI implementation, it still does not solve for building an end-to-end workflow on its own. To integrate AI into enterprise workflows, we must first do the foundation work to get our clients’ data estate optimized, structured, and migrated to the cloud. This data engineering step is critical because it sets up the formal process through which analytics tools will continue to be informed – even as the underlying models keep evolving over time. It requires the ability to break down silos between disparate data sets and keep data flowing in real-time. Once the data foundation is in place, it is important to then select and embed the best combination of AI models into the workflow to optimize for cost, latency, and accuracy.  At EXL, our repertoire of AI models includes advanced pre-trained language models, domain-specific fine-tuned models, and intelligent AI agents suited for targeted tasks. These models are then integrated into workflows along with human-in-the-loop guardrails.  This process not only requires technical expertise in designing the most effective AI architecture but also deep domain knowledge to provide context and increase the adoption to deliver superior business outcomes. EXL The goal here is to make AI integration feel completely seamless to end users. They should not be jumping in and out of different tools to access AI; the technology needs to meet them where they are in the existing applications they’re already using. For example, EXL is currently working on a project with a multinational insurance company designed to improve underwriting speed and accuracy with AI. At its core, that process involves extracting key information about the individual customer, unstructured data from medical records and financial data and then analyzing that data to make an underwriting decision. We created a multi-agent solution where one agent used specialized LLMs for data extraction alongside our EXL Insurance LLM for data summarization and insight generation. Meanwhile, a separate AI agent used machine learning and analytics techniques to make underwriting and coverage decisions based on the outputs from the first model. So, by orchestrating, engineering, and optimizing the best combination of AI models, we were able to seamlessly embed AI into underwriting workflows without adding excessive data processing costs.  Similarly, we orchestrated and engineered another multi-agent solution for a leading bank in the U.S. to autonomously address lost card calls. Strategic AI orchestration is the real

By Dorothy Atkins ( December 6, 2024, 4:26 PM EST) — OpenAI Inc. informed New York and California federal courts this week it plans to ask the Judicial Panel on Multidistrict Litigation to centralize eight copyright infringement and Digital Millennium Copyright Act lawsuits — including a proposed class action — brought by content creators and publishers…. 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 Aaron Keller ( December 9, 2024, 4:20 PM EST) — The ousted leader of WorldQuant Predictive Technologies LLC lost $6 million in company stock because he was legitimately fired for lying during a company probe into a lead salesperson’s termination and not because of an alleged legal ethics gaffe, Connecticut law firm Pullman & Comley told a judge on Monday…. 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