By Al Barbarino ( October 25, 2024, 5:11 PM EDT) — Frontier Communications on Friday urged shareholders to support its planned $20 billion sale to Verizon, calling the $38.50 per-share price tag “highly attractive” despite mounting opposition from top investors, one of which claimed the company may be worth double that…. 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

TL;DR: Get lifetime access to The 2024 All-in-One Ethical Hacking Course Bundle for just $44.99 and start mastering ethical hacking techniques to protect and secure networks. The 2024 All-in-One Ethical Hacking Course Bundle is a must-have for professionals and aspiring cybersecurity experts looking to enhance their skills in a rapidly evolving field. With 18 comprehensive courses totaling 92 hours of self-paced content, this bundle provides everything you need to dive deep into ethical hacking, penetration testing, and network security. We all know too well that data breaches and cyberattacks are more frequent and sophisticated than ever before. According to Cybersecurity Ventures, “cybercrime is expected to cost the world $10.5 trillion annually by 2025, up from $3 trillion in 2015.” This highlights the increasing demand for cybersecurity professionals who can safeguard sensitive information and prevent unauthorized access to systems. Priced at just $44.99 (regularly $719), this bundle equips you with hands-on knowledge and practical experience using essential tools like Nmap, Metasploit, and Wireshark. The courses cover a wide range of cybersecurity topics, making it ideal for anyone looking to start a career as a security analyst, penetration tester, or IT security specialist. What’s included Whether you’re a newcomer to the world of cybersecurity or a professional looking to deepen your expertise, the 2024 Ethical Hacking Course Bundle offers practical training that can help you advance your career. Each course is designed to equip you with the knowledge and skills to identify and patch vulnerabilities, protect sensitive data, and ensure systems remain secure. One of the standout courses in this bundle is the Complete NMAP Course, where you’ll master the art of network discovery and security auditing. Whether you’re scanning a network for open ports or identifying active devices, the skills learned in this course will be invaluable in day-to-day IT security roles. Take a look at all 18 courses to see if this is something that could support your journey. The 2024 All-in-One Ethical Hacking Course Bundle is just $44.99 (reg. $719) for a limited time. Prices and availability subject to change. source

The walking, talking, dancing Optimus robots at the recent Tesla demonstration generated huge excitement. But this turned to disappointment as it became apparent that much of what was happening was actually being controlled remotely by humans. As much as this might still be a fascinating glimpse of the future, it’s not the first time that robots have turned out to be a little too good to be true. Take Sophia, for instance, the robot created by Texas-based Hanson Robotics back in 2016. She was presented by the company as essentially an intelligent being, prompting numerous tech specialists to call this out as well beyond our capabilities at the time. Similarly we’ve seen carefully choreographed videos of pre-scripted action sequences like Boston Dynamics’ Atlas gymnastics, the English-made Ameca robot “waking up”, and most recently Tesla’s Optimus in the factory. Obviously these are still impressive in different ways, but they’re nowhere near the complete sentient package. Let Optimus or Atlas loose in a random home and you’d see something very different. A humanoid robot capable of working in our homes needs to be capable of doing many different tasks, using our tools, navigating our environments and communicating with us like a human. If you thought this was just a year or two away, you’re going to be disappointed. Building robots able to interact and carry out complex tasks in our homes and streets is still a huge challenge. Designing them even to do one specific task well, such as opening a door, is phenomenally difficult. There are so many door handles with different shapes, weights and materials, not to mention the complexity of dealing with unforeseen circumstances such as a locked door or objects blocking the way. Developers have actually now created a door-opening robot, but robots that can deal with hundreds of everyday tasks are still some way off. Behind the curtain The Tesla demonstration’s “Wizard of Oz” remote operation technique is a commonly used control method in this field, giving researchers a benchmark against which to test their real advances. Known as telemetric control, this has been around for some time, and is becoming more advanced. One of the authors of this article, Carl Strathearn, was at a conference in Japan earlier this year, where a keynote speaker from one of the top robotics labs demonstrated an advanced telemetrics system. It allowed a single human to simultaneously operate many humanoid robots semi-autonomously, using pre-scripted movements, conversation prompts and computerised speech. Clearly, this is very useful technology. Telemetric systems are used to control robots working in dangerous environments, disability healthcare and even in outer space. But the reason why a human is still at the helm is because even the most advanced humanoid robots, such as Atlas, are not yet reliable enough to operate completely independently in the real world. Another major problem is what we can call social AI. Leading generative AI programs such as DeepMind’s Gemini and OpenAI’s GPT-4 Vision may be a foundation for creative autonomous AI systems for humanoid robots in the future. But we should not be misled into believing that such models mean that a robot is now capable of functioning well in the real world. Interpreting information and problem solving like a human requires much more than just recognising words, classifying objects and generating speech. It requires a deeper contextual understanding of people, objects and environments – in other words, common sense. To explore what is currently possible, we recently completed a research project called Common Sense Enhanced Language and Vision (CiViL). We equipped a robot called Euclid with commonsense knowledge as part of a generative AI vision and language system to assist people in preparing recipes. To do this, we had to create commonsense knowledge databases using real-world problem-solving examples enacted by students. Euclid could explain complicated steps in recipes, give suggestions when things went wrong, and even point people to locations in the kitchen where utensils and tools might typically be found. Yet there were still issues, such as what to do if someone has a bad allergic reaction while cooking. The problem is that it’s almost impossible to handle every possible scenario, yet that’s what true common sense entails. This fundamental aspect of AI has got somewhat lost in humanoid robots over the years. Generated speech, realistic facial expressions, telemetric controls, even the ability to play games such as “rock paper scissors” are all impressive. But the novelty soon wears off if the robots are not actually capable of doing anything useful on their own. This isn’t to say that significant progress isn’t being made toward autonomous humanoid robots. There’s impressive work going on into robotic nervous systems to give robots more senses for learning, for instance. It’s just not usually given the same amount of press attention as the big unveilings. The data deficit Another key challenge is the lack of real-world data to train AI systems, since online data doesn’t always accurately represent the real-world conditions necessary for training our robots well enough. We have yet to find an effective way of collecting this real-world data in large enough quantities to get good results. However, this may change soon if we can access it from technologies such as Alexa and Meta Ray-Bans. Nonetheless, the reality is that we’re still perhaps decades away from developing multimodal humanoid robots with advanced social AI that are capable of helping around the house. Maybe in the meantime we’ll be offered robots controlled remotely from a command centre. Will we want them, though? In the meantime, it’s also more important that we focus our efforts on creating robots for roles that can support people who urgently need help now. Examples would include healthcare, where there are long waiting lists and understaffed hospitals; and education, to offer a way for overanxious or severely ill children to participate in classrooms remotely. We also need better transparency, legislation and publicly available testing, so that everyone can tell fact from fiction and help build public trust for

offer suggestions on how the call could be done better analyze projects and processes to suggest improvements create personas that we will ask business questions to, eventually leading to organizational digital twins These are just a few examples of how AI, rather than automating employees out of existence, can enhance employees and businesses. Last, businesses need to prioritize different elements of AI experience for users versus customers. For customers, choice is crucial. Businesses should offer human-like AI to help customers, but customers should also have the choice of direct interaction with a person. For users, accuracy is paramount. AI doesn’t need to be human-like, especially when it is supplementing employees’ work, but it needs be accurate, so users are getting enhancements to their abilities rather than more work and poor experience. Lead with design, acceptance follows It probably comes as no surprise that the Horsey Horseless, the car with the wooden horsehead on the hood, was never a success. Quick fixes are not enough to promote public acceptance of new technology. Instead, we need to focus on developing clear use cases that offer real value for people while providing a seamless, great experience. source

By Katherine Smith ( October 29, 2024, 12:02 PM EDT) — Ambika Kumar of Davis Wright Tremaine LLP has worked on multiple high-profile online free speech cases, including successfully halting a groundbreaking California law surrounding online privacy protections for children, earning her a spot as one of the 2024 Law360 Technology MVPs…. 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

Over the past two years, the market has been flooded with sparkly artificial intelligence tools that promise to improve our writing. Generative AI’s primary function is content creation, and chatbots are its most accessible form, so it is not surprising that the number of so-called “copilots” has grown quickly. However, many are based on the same large language models and produce varying results. It is widely accepted that, without the human touch, AI favours cliched, repetitive content. This is especially the case for tasks used in a professional setting, such as drafting emails and marketing content. Saying that, bespoke AI writing aids can be beneficial when used correctly. They can significantly speed up tasks, highlight grammatical errors you didn’t notice, keep your copy’s style on-brand, formulate scattered ideas, and help you overcome writer’s block. The best tools will also gear the user away from generic content that both puts off readers and flags AI detectors. To help writers cut through the noise and find the AI that will do the best with the task at hand, TechRepublic has compiled a list of the top five tools for different writing tasks. SEE: Scale Your SEO Writing With This AI-Powered Tool for Google Sheets Best AI writing tools: Comparison table Tool What it does Cost LLM Grammarly Checks spelling, grammar, clarity, and style. Free for basic plan. Proprietary. ChatGPT Powerful, multipurpose chatbot. Free for basic plan. GPT-4. Jasper Produces written and visual content in a brand’s style. $39/£30 per month, per user. GPT-4. Flowrite Writes emails, social media posts, and other everyday messages. $5/£4 per month for 15 messages. GPT-3. DeepL Translate Accurately translates text into 30+ languages. Free to translate up to 25,000 characters a day; $28.74/£22.18 per month for unlimited. Proprietary. Best for spelling and grammar: Grammarly The Grammarly widget suggests spelling, grammar, and style changes as you write. Image: Grammarly/Screenshot by TechRepublic Grammarly is one of the most well-known writing aids. It has been around since the pre-ChatGPT era, aiding users with their spelling and grammar wherever they’re typing, be it Word, Gmail, Teams, or just their to-do list. Additionally, the Grammarly widget will include suggestions on sentence structure, style, and clarity, on top of highlighting the typical typos and misplaced apostrophes. You can apply these edits with just a click. This writing tool goes deeper with its suggestions than a simple spellchecker, especially if you upgrade to Pro level. One of the coolest things I’ve noticed is how it can direct you away from unconscious biases in your writing, such as suggesting “spokesperson” over “spokesman.” But it can also highlight “weak” choices of adjectives and when a more optimistic, convincing, formal, or otherwise appropriate word could be used within the context of the sentence. Grammarly is more powerful than other AI writing assistants, in part, because it uses a proprietary LLM, rather than relying on offerings from OpenAI or another tech giant. Plus, if you like chatbots, it has also recently added the GrammarlyGO writing assistant that can respond to prompts based on your text. Price Free for basic plan. Pro level costs $12/£10 a month and includes plagiarism detection, tone adjustment, sentence rewriting, and more. Top features Spellchecker, plagiarism checker, personalised weekly email with writing stats. Pros and cons Pros Cons Regarded as the most accurate tool for spelling and grammar. Poor for fiction writing. Provides explanations with each suggestion. Over-reliance can make text read generically. Best for generating ideas: ChatGPT ChatGPT is useful for writers looking for starting points or fleshing out ideas. Image: OpenAI/Screenshot by TechRepublic By now, it would take a dedicated technophobe to have not heard of OpenAI’s ChatGPT. The chatbot has become almost synonymous with generative AI, since its release in November 2022 brought the power of the technology into the public consciousness. While it has brought about much valid criticism regarding its hallucinations, biases, security issues, and environmental impact, it can certainly prove helpful when writing if used responsibly and smartly. ChatGPT’s intelligence means that it can interpret disparate ideas or half-baked questions, so it is useful for brainstorming. For example, if there’s a word on the tip of your tongue, you can prompt the bot with what it sounds like, the letter it starts with, and a general definition, and it is likely you’ll get your answer. The chat interface makes it easy to build on ideas, and the LLM’s wide breadth of knowledge means it can give you a starting point for almost any topic. However, those that use ChatGPT regularly can quite easily spot its telltale signs; lists of threes, bullet point lists, “in the ever-evolving landscape,” to name just a few. This means that it is unwise to copy and paste large chunks of outputted text without any amendments. ChatGPT’s ideas are also often basic and vague, as everything it generates is based on already-published text, so use with caution. SEE: ChatGPT vs Google Gemini (2024): What Are the Main Differences? Price Free, for the most part. If you would like access to OpenAI’s most powerful LLMs, then you will need at least a “ChatGPT Plus” membership, costing $20/£16 a month. Top features GPT-4 access, DALL-E image generation for paid users. Pros and cons Pros Cons One of the most intelligent LLMs available for personal use. Its default output is recognisable in style, so should be edited before publication. Useful for overcoming writer’s block, as it can suggest starting points. Prone to inaccuracies when asked factual questions. Best for creating marketing content: Jasper Jasper is a content-generating tool especially for marketers. Image: Jasper/Screenshot by TechRepublic Unlike ChatGPT and Grammarly, Jasper is intended to aid writers working in a specific industry: marketing. Users will feed it information about the company, be it tone of voice or product details, as “memories” to draw from. Then, its chatbot interface can respond to prompts asking for blog and social media posts, product descriptions, emails, scripts, and other marketing content. On top of being knowledgeable of the products and services, Jasper’s

“Every enterprise must assess the return on investment (ROI) before launching any new initiative, including AI projects,” Abhishek Gupta, CIO of India’s leading satellite broadcaster DishTV said. “It’s essential to evaluate all AI initiatives using the same criteria. Once a specific business use case for AI is identified, a thorough cost estimation should be conducted and compared against the anticipated business outcomes to ensure alignment and value. Without a precise understanding of how AI expenses scale, companies risk underestimating costs by as much as 1,000%, making financial missteps that could cripple broader technology initiatives, Gartner said. “As a CIO, you need to understand your AI bill,” LeHong stressed. “You must understand the cost components and pricing model options, and you need to know how to reduce these costs and negotiate with vendors. CIOs should create proofs of concept that test how costs will scale, not just how the technology works.” source

In B2B organizations, process is the unsung hero in delivering strategic initiatives and business outcomes, yet processes are often overlooked and poorly managed, leading to struggles with process design, implementation, adoption, and optimization. Processes often develop organically within functional or subfunctional silos — without much forethought — and become a negative experience for all participants. In mature organizations, operations and process leaders are responsible for process optimization projects and change management efforts across go-to-market teams to ensure streamlined, cross-functional processes. We interviewed 20 clients who provided thoughtful and actionable feedback for how their go-to-market operations teams mitigate six red flags to achieve operational excellence across B2B teams. The full report provides a comprehensive analysis of the six red flags, including detailed breakdowns, numerous warning signs to look out for, their meanings, and tactical strategies to mitigate their impact. Identify these warning signs in your organization’s processes and turn those red flags green before it’s too late. 1. Red Flag: Processes Inefficiently Designed And Documented Processes are often nonexistent, unclear, inadequate, or fail to serve their purpose. Warning signs: Complex and overengineered Too vague or too detailed   2. Red Flag: Processes Undergoing Constant Change Frequent changes to processes beget an unstable work environment. Warning signs:   3. Red Flag: Processes Lacking Clear Roles, Expectations, And Accountability Chaos ensues when no one knows who owns the process, who should be involved, or what everyone is supposed to do. Warning signs:   4. Red Flag: Processes Missing End-To-End Workflows By Participant Role Murky handoffs within and between B2B processes reveal deeper issues within the organization’s structure and communication. Warning signs: Not aligned with company goals and objectives Inability to determine where issues lie   5. Red Flag: Processes Deprived Of Adequate Compliance B2B organizations face significant challenges when people don’t adhere to processes. Warning signs: Rogue duplicative processes   6. Red Flag: Processes Not Being Measured Without success metrics, organizations can’t determine whether they’re on the right track or if adjustments are needed. Warning signs: Inconsistent quantifiable metrics   If some of these red flags feel inevitable, you are not alone. Many B2B organizations struggle with their processes, but operational excellence and improved business outcomes can be achieved when the go-to-market operations team takes the lead in designing, documenting, and optimizing processes. The first step is to raise the alarm bells when you see a warning sign. Identify any gaps before they grow into a true red flag. The final step is mitigation. Find the answers in the full report, which dives deeper into what each red flag really means for your organization along with actionable insights for prevention. (Riley McDonnell, research associate, contributed to this post.) source

Yes, virtual private networks are worth it. In today’s digital age, it’s become increasingly important to protect online data. In the fourth quarter of 2023 alone, more than eight million data records were exposed to data breaches all over the world. VPNs address this by encrypting the connection between a device and an online network, securing data against hackers and bad actors. While quality VPNs typically require a paid subscription, they are relatively inexpensive compared to possible losses incurred from a breach or a cyberattack. IBM reported that the global average cost of a data breach this year can reach $4.45 million. In this article, we’ll offer reasons why VPNs are worth the spend, how free VPNs fare against paid ones and what VPN services can be best for you and your business. ESET PROTECT Advanced 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 Advanced Threat Defense, Full Disk Encryption , Modern Endpoint Protection, and more ManageEngine Log360 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), Medium (250-999 Employees), Enterprise (5,000+ Employees), Large (1,000-4,999 Employees), Small (50-249 Employees) Micro, Medium, Enterprise, Large, Small Features Activity Monitoring, Blacklisting, Dashboard, and more What does a VPN do? A VPN protects your online traffic by generating a secure and encrypted tunnel which all your data is passed through. This hides your online activity and makes your data illegible to malicious third parties. VPNs protect sensitive information such as IP addresses, browsing history, DNS queries, files downloaded, and other types of personal data. SEE: Does a VPN Slow Down Your Internet Speed? (TechRepublic) VPNs also give you the ability to select an alternate IP address and location and access region-blocked websites. This allows you to view geo restricted content like streaming services, news articles, and locked websites. To learn more about VPNs, you can check out our full article entitled What is a VPN? Why you need a VPN for your business VPNs are a cost-effective way to ensure that your business’ data is protected against cyberattacks and hackers. As more organizations rely on the internet for their regular operations, it’s important to be proactive in securing internal resources. Confidential information like inventories, business strategies, and internal communications are just a few examples of data that VPNs can protect. SEE: How Much Does a VPN Cost? + Savings Tips (TechRepublic) VPNs also bring an additional layer of security to client/s’ confidential data. Through VPN encryption, you can ensure customers that their information is in safe and secure hands. Additionally, VPNs help secure resources for employees that access a company’s network remotely. As more organizations shift toward hybrid setups, VPNs ensure that no data is accidentally exposed when remote employees access materials on the company network. What is the downside of having a VPN? While using a VPN adds a layer of security, there are a few drawbacks that come with it. Perhaps the biggest disadvantage is slower VPN speeds or higher latency. Since a VPN encrypts your online traffic and routes it to a VPN server, additional steps are added to the overall path of your connection. With these additional steps, your internet speed is likely to get slower compared to when you’re directly connected to your internet service provider. Fortunately, most quality VPNs will only have a 10-30% decrease in VPN speed that is almost negligible in real-world use. SEE: How to Tell If Your VPN Is Working Properly (TechRepublic) There’s also a danger of errant VPNs doing the opposite of protecting user data. Usually done by free VPNs, some providers will outright log or record your data and sell it to third party agencies or marketing companies. This is why it’s important to use a VPN with a no-logs policy that’s been independently verified. You can check out our rundown of the best no-logs VPNs here. Finally, online sites or services may block or restrict VPNs altogether. Examples of websites that may not play well with VPNs are streaming services or social networking sites. Free vs. paid VPNs Free VPNs Paid VPNs No payment information required Requires a monthly payment Limited security, speed and features Heightened security and performance Only offers a handful of servers Full server network Free VPNs offer access to an encrypted connection at zero cost. Because they’re free, they don’t require users to hand over financial information, such as credit card numbers or bank details. Some paid VPN providers even offer free tiers of their services. This is a great way to trial a particular vendor’s VPN implementation before purchasing a subscription. However, there are drawbacks to free VPNs — chief among these is the limited security and performance. Most free VPNs possess weaker overall encryption and have a smaller network of servers. It’s also common for free VPNs to restrict connection speeds and have a cap of only 2-5 GB of usable data per month. Because the service is free, there’s a good chance that free VPNs sell your data to marketing companies to make up the costs. SEE: Free VPN vs Paid VPN: Which One Is Right for You? (TechRepublic) Paid VPNs address all of these issues. They offer the highest quality of encryption and security, grant you access to a full server suite, and typically provide more reliable performance and speed. With a paid VPN subscription, you also get extra security features such as built-in anti-malware protection, ad-blocking, and specialized servers for streaming or torrenting. Paid services usually offer more robust independent testing on their security claims. While most VPNs carry no-logs policies on user data, not all vendors back these claims through third-party audits. On the same note, paid VPNs are also less incentivized to sell your data since they already make a profit through monthly subscription fees. Other benefits of paid VPNs over free VPNs are better customer service, more intuitive user interfaces, and support for multiple platforms. More cloud

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Moondream emerged from stealth mode today with $4.5 million in pre-seed funding and a radical proposition: when it comes to AI models, smaller is better. The startup, backed by Felicis Ventures, Microsoft’s M12 GitHub Fund, and Ascend, has built a vision-language model that operates with just 1.6 billion parameters yet rivals the performance of models four times its size. The company’s open-source model has already captured significant attention, logging over 2 million downloads and 5,100 GitHub stars. “What makes it special is that it is one of the tiniest models that is peculiar in its high accuracy, and it works just really well,” said Jay Allen, Moondream’s CEO and former AWS tech director. “It can run everywhere really easily and quickly. It can even run on iOS, on mobile phones.” Edge computing meets enterprise AI: How Moondream solves the cloud cost crisis The startup tackles a growing problem in enterprise AI adoption: the astronomical costs and privacy concerns of cloud computing. Moondream’s approach allows AI models to run locally on devices, from smartphones to industrial equipment. “As AI makes its way into more and more apps, I think we’re kind of torn between wanting all the benefits of the AI, but not necessarily wanting our entire lives broadcast to the cloud,” Allen told VentureBeat. “My preference is to do as much close to the edge so I have control over my own privacy.” Real-world applications: From retail inventory to factory floor intelligence Early adopters have found diverse applications for the technology. Retailers use it for automatic inventory management through mobile scanning. Transportation companies deploy it for vehicle inspections, while manufacturing facilities with air-gapped systems implement AI locally for quality control. The technical achievements stand out. Recent benchmarks show Moondream2 achieving 80.3% accuracy on VQAv2 and 64.3% on GQA — competitive with much larger models. The system’s energy efficiency impresses, with CTO Vik Korrapati noting “per token consumption is something like 0.6 joules per billion parameters.” David vs. Goliath: How a Small Team Takes On Tech Giants While major tech companies focus on massive models requiring substantial computing resources, Moondream targets practical implementation. “A lot of companies in this space are focused on AGI, and that ends up becoming a big distraction,” Korrapati said. “We’re laser focused on the perception problem and how we deliver cutting edge multimodal capabilities in the size and form factor that developers need.” The company now launches Moondream Cloud Service, designed to simplify development while maintaining flexibility for edge deployment. “What they want is the easiest path to start with a cloud-like offering so they can just play around with it,” Allen said. “But once they’ve done that, they don’t want to feel like they’re locked in.” This hybrid approach resonates with developers. The company has built a strong following in the open-source community, with Allen attributing this to their “hacker, open source ethos” and transparent development process. As for competition from tech giants, Allen remains confident in Moondream’s focused strategy. “For a lot of these large companies, this tends to be one of their 8,000 priorities,” he said. “There doesn’t seem to be a lot of companies that are as singularly focused as we are on providing a seamless developer experience around multimodal.” The company expects widespread enterprise adoption of vision language models within the next 12 months, though Korrapati cautions that “talking about timelines with AI is a dangerous game.” With the fresh funding, Moondream plans to expand its team, including hiring fullstack engineers at its Seattle headquarters. The company’s next challenge will be scaling its technology while maintaining the efficiency and accessibility that have defined its early success. source