By Hayley Fowler ( January 17, 2025, 8:43 PM EST) — A North Carolina federal judge didn’t mince words in rejecting a joint request from opposing parties in an upcoming redistricting trial who sought a reprieve from a local rule largely barring electronics in the courthouse, saying “nobody needs a cellphone in the courtroom.”… 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

由新鴻基地產（新地）發展的西沙大型綜合發展項目的運動商業綜合部分「西沙GO PARK」今日舉行啟動禮，標誌著這個佔地130萬平方呎、集室外與室內運動、娛樂、餐飲及休閒體驗於一身的全新地標正式啟用。 政務司司長陳國基、中央人民政府駐香港特別行政區聯絡辦公室副主任祁斌、新鴻基地產主席兼董事總經理郭炳聯、新鴻基地產代理有限公司資深董事郭炳江、新鴻基地產執行董事郭基煇及新鴻基地產執行董事郭基泓擔任開幕禮主禮嘉賓，聯同、多位共創明「Teen」計劃師友，約一千名嘉賓、學生和老師一同見證香港迎來嶄新地標。 新鴻基地產主席兼董事總經理郭炳聯表示：「西沙項目是新地耗時數十年、近年最大型的綜合發展項目之一，當中西沙GO PARK將成為香港的全新地標。新地秉承『以心建家』信念，矢志發揮西沙周遭有山有水的秀麗景色，打造西沙GO PARK成為每個香港人的後花園，既可讓普羅大眾享受運動樂趣，亦適合三代同堂、連同家中寵物共享天倫之樂的新地標，不僅惠及周邊社區，亦吸引全港市民到訪。」 為推廣西沙GO PARK全民運動理念，開幕禮特別邀請共創明「Teen」計劃學員共同見證，並與奧運劍擊金牌得主江旻憓即場試玩新興運動匹克球（Pickleball），場面熱鬧歡快。新地作為共創明「Teen」計劃的策略夥伴之一，早前亦邀請約70名共創明「Teen」師友到西沙GO PARK試玩多項新興運動，擴闊學員眼界，發掘個人興趣與潛能。 政務司司長陳國基表示：「我要衷心感謝新鴻基地產一直以來對共創明『Teen』計劃的鼎力支持。新地一直致力履行社會責任，今天的活動正正是新地『以心建家』信念的體現。我們不單看到新鴻基地產對基層學生的支持，也看到他們對建設關愛共融社會的熱誠。在政、商、民三方繼續通力合作下，我深信我們一定能夠為我們下一代的成長、成才，創造一片更美好的藍天。」 新鴻基地產執行董事郭基煇表示：「GO PARK 善用附近漂亮的海岸線，以及鄰近西貢的島嶼和郊野公園，完美結合體育、行山、水上活動、零售及旅遊度假全方位體驗。作為全港唯一一個由私營機構營辦並對公眾開放的體育學院，GO PARK不僅有完善的硬件設施，更夥拍了十多個體育總會、知名體育學院等舉辦不同課程，推動全民運動、體育普及化、精英化、產業化，也正好符合政府全方位推動文化、體育及旅遊盛事發展的方向，助力香港成為國際體育盛事之都。」 新地持續支持共創明「Teen」計劃，過去兩期均有逾200名新地員工擔任計劃的友師，亦有捐款及舉辦多項不同類型的活動，協助學員找到自己的發展道路，新一期新地有逾200名員工報名擔任共創明「Teen」計劃的友師。 西沙GO PARK開創全新運動商業綜合體   推動香港體育發展新里程 西沙GO PARK佔地共130萬平方呎，以「公園式運動商業綜合體」為設計概念，由全球知名的扎哈‧哈迪德建築事務所（Zaha Hadid Architects）操刀，融合大自然形態的流線形設計於充滿未來感的建築之中，是集運動、娛樂、餐飲及休閒體驗於一身的嶄新地標。  西沙GO PARK劃分為兩大部份——100萬平方呎的多元化戶外運動公園 「GO PARK Sports」以構建面向公眾的體育學院為定位，提供十多個符合國際專業規格的體育設施，涵蓋熱門、城市和新興運動，適合一家大小以至專業的運動參與者，共同享受健康生活的樂趣，場地現正式對外開放予公眾人士透過手機應用程式「GO PARK Sports 」及網頁進行預約及租用；而30萬平方呎的「運動商業綜合部分」匯聚多間運動消閒及餐飲娛樂商戶，包括能容納1,500人、擁有一流設計和設備的多用途室內主場館；佔地共逾４萬平方呎的三大兒童遊樂區；逾３千呎的寵物公園，亦包括全天候室內游泳池、劍擊學校、健身中心、室外攀石牆等設施場地，共同實現身心靈健康、寵物友善、跨代共融的宗旨，凝聚各種興趣的社群，營造西沙充滿活力的現代社區生活。 全新水上活動中心「GO PARK Aqua」 與此同時，西沙GO PARK將增添全新水上活動中心「GO PARK Aqua」，預計快將試業。項目佔地13萬平方呎，充分展現西沙倚山傍海、擁有獨特海岸資源的特色，將與多個運動總會及機構合作，提供各類水上活動的課程與體驗，另外更設有多元化生活品味工作坊，讓一家大小輕鬆展開豐富精彩的探索之旅。此外，項目於海岸線設置別具特色的「巨型拍照相框」，可供訪客拍攝獨特打卡美照。 圖片說明： 一眾主禮嘉賓，為西沙 GO PARK 開幕 x  共創明「TEEN」進行啟動儀式，左起為：共創明「Teen」學員梁佩詩、新鴻基地產執行董事郭基煇、新鴻基地產代理有限公司資深董事郭炳江、政務司司長陳國基、新鴻基地產主席兼董事總經理郭炳聯、中央人民政府駐香港特別行政區聯絡辦公室副主任祁斌、新鴻基地產執行董事郭基泓、共創明「Teen」學員張家朗及符文豪。 LinkedIn Email Facebook Twitter WhatsApp source

Agentic AI promises to transform enterprise IT work. For CIOs and IT leaders, this means improved operational efficiency, data-driven decision making and accelerated innovation. Agentic AI’s ability to assess changing conditions in service operations (ServiceOps) and proactively recommend steps to reduce change failures sets the technology apart from traditional AI and automation tools. But before we explore the potential impact of agentic AI on ServiceOps, let’s look at the change approval process in most large enterprises. Traditionally, the manager from the change advisory board (CAB) coordinates the teams and stakeholders, makes final decisions to approve or reject proposed changes, and directs the implementation of changes. However, the DevOps teams that release new features constantly within the same organization don’t go through the traditional change approval process. DevOps may push thousands of changes daily, and the CAB process is simply too slow. DevOps teams follow their own practices of using continuous integration and continuous deployment (CI/CD) tools to automatically merge code changes and automate testing steps to deploy changes more frequently and reliably. The lack of a single approach to delivering changes increases the risk of introducing bugs or performance issues in production. When change occurs, organizations often lack the visibility and understanding of the change’s impact on the organization’s IT ecosystem. With the complexity of modern business operations and the accelerated pace of change driven by DevOps, organizations face a growing demand for a simpler way for IT service and operations teams to balance speed and risk. Agentic AI and the new AI agent Some of the most exciting capabilities of agentic AI are its ability to interact with a wide variety of tools and data, generating insights, and executing tasks in a proactive manner. Imagine an AI agent specifically designed to guide change management and DevOps teams to deploy system and software changes more rapidly and reliably. The AI agent proactively identifies risky changes by analyzing operations and service management data together, providing a change risk score, summarizing the insights, and recommending best actions — all in one place. With this information, teams can ask the AI agent additional questions such as “Should I approve the change?” or “Can I look at similar changes?” Using an AI agent, the CAB and DevOps teams get the answers needed to confidently determine the next best actions. For example, when a database upgrade is requested, the Change Risk Advisor AI agent within BMC Helix AIOps gathers historical operations and service data relevant to the database service, helping IT teams understand the risk of deploying the change. The Change Risk Advisor AI agent combs through past situations or problems and assesses the current service health status to recommend the best actions. If further due diligence is recommended, change management or DevOps teams can interact with the AI agent to ask further questions like “Who is the change owner?” or “Can I look at change collision?” Visibility into the real-time deployment landscape and additional context around the change enables both the CAB and DevOps teams to collaborate and apply better actions that reduce change failures. GenAI and agentic AI: The future of ServiceOps Generative AI (GenAI) and agentic AI play a powerful role in ServiceOps. When used to complement predictive and causal AI, service and operations teams can use AI-based risk assessment for changes. BMC ServiceOps offers a new operating model for accelerating change while predicting and managing risk across the enterprise. By integrating data and workflows between ITSM and AIOps tools, the BMC HelixGPT Change Risk Advisor agentic AI agent enables smarter, data-driven decision making. With agentic AI, CAB and DevOps teams get: Insights and recommendations throughout the entire change process Proactive change risk predictions for all changes Reduced outages caused by high-risk changes Accelerated change deployment without change anxiety Higher success rates by lowering change failures Moving forward We’re in a new era of AI service operations and management. BMC Helix is already paving the path for successful outcomes with BMC HelixGPT, an agentic system integrated into the BMC Helix Platform that powers ServiceOps. Discover how agentic AI can simplify change management and transform ServiceOps into a proactive force that improves business results in your organization. Visit here for more information or contact BMC. source

By Jade Martinez-Pogue ( January 17, 2025, 6:39 PM EST) — Blank-check company Hennessy Capital Investment Corp. VII began trading publicly on Friday after raising $175 million in its initial public offering, which will be used to merge with a company in the industrial technology or energy transition sectors…. 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

Is a Super Bowl ad worth it? A 30-second spot at this year’s Super Bowl will set you back a cool 7 million bucks. And even if you wanted one of those spots, you can’t have it — they’ve been gone for a while. That must mean these ads are like the proverbial goose laying golden eggs, right? Wrong! Can a Super Bowl ad spot be a sensible investment? Perhaps in some cases, like for a low-awareness brand that needs a jolt of awareness or for a brand making a pivot that it needs a lot of people to know about. But has it worked out for all the blue-chip brands that gobble up the ad space as soon as it hits the market? We decided to check out a few brands that advertised in 2024 (most of which plan to advertise again in 2025) and see how they fared after their Super Bowl campaign. Do Super Bowl campaigns create shareholder value? Attribution analysis of advertising spend can be extremely complex and messy, and that’s not what we are doing here. Instead, we want to see if the brands that advertised did well for their shareholders in the months following the Super Bowl. We compare the stock price of the advertised brand with that of a close peer, and then we throw in the S&P 500 (to measure against overall market movement) and, if available, an industry index (to compare against the category). Here’s how to easily read the charts below: The advertised brand is in green, the competitive brand is in orange, and the market or category indices are in black and gray. We’ve indexed the prices back to the day of Super Bowl 2024 so you can easily compare the advertised brand’s market performance versus that of the others. Seven million dollars later … Here are the findings for the four brands we analyzed:   Intuit has advertised its free online and premium paid tax software (Turbo Tax) in every Super Bowl since 2014 and plans to do so again in 2025. Since its 2024 Super Bowl ad, the company has consistently lagged the S&P 500 and, worse yet, significantly fallen short of its competitor, H&R Block, which has outperformed the market for most of the year. In 2024, Toyota featured the Tacoma in its Super Bowl ad. The year has not been kind to the automobile industry, whose category stock performance has fallen well below the S&P. Toyota did stay ahead of the industry but, for the most part, trailed Honda’s performance. Doordash has been advertising its delivery platform since 2022 and plans to do so again in Super Bowl 2025. After its 2024 campaign, which included a sweepstakes, Doordash pushed ahead of the S&P for a bit but since has had mixed results in beating the market, and unfortunately, it has trailed Grubhub by significant margins for the best part of the year following the Super Bowl. Booking Holdings, like Doordash, has been advertising at the Super Bowl since 2022 and will be back in 2025. Immediately following the Super Bowl, its stock trailed the market and Expedia for a couple of months, made up some ground through the summer months, and since then has closely tracked Expedia. There is little in Booking Holdings’ stock performance to indicate a lift from the Super Bowl. Ouch! What’s a marketer to do? Granted that more analysis needs to be done to truly determine the ROI of a Super Bowl ad (or, for that matter, any ad), but when you sink that much money into an ad campaign and your stock has nothing to show for it, it raises red flags. There are two stark lessons here for any marketer planning a campaign of any size or significance: You are ultimately answerable to the shareholder (or equivalent stakeholders in private companies) for whom you create value, so you must orient your metric around demonstrating outcomes for the enterprise. That’s how you demonstrate your utility to the business. You better be buttoned up on the numbers if you’re pitching marketing campaigns in an environment where your company performance clearly trails your peers. Can you prove that this is the best use of money compared to everything else the company could do with those funds? If I were the CMO at any of these companies that are limping along despite massive ad spend, I’d be telling my CEO that we would be far worse off if we did not make that marketing investment. But, and this is a big but, I’d have to have the numbers to back it up. Better yet, I’d make sure those numbers came with my CFO’s stamp of approval. (Tyler Castro contributed to the analyses and research for this post.) Learn more: Forrester clients can read my research on how brands grow. Follow my work: Go to my Forrester bio and click “Follow.” Chat with me: If you are a Forrester client interested in discussing these topics, please schedule time with me for an inquiry or a guidance session. Plan a session: If you are a Forrester client looking to host a strategy session on a related topic (for example, “the future of digital consumer experience related to AI”), please contact your account team or email me at [email protected]. source

An Icelandic scaleup has sparked hopes of a breakthrough in dementia treatment after raising €26.5mn for groundbreaking research. Arctic Therapeutics (ATx) attracted the investment after pioneering a new approach to drug development. Founded in 2015, the company first analyses genomic data with bioinformatics — a blend of computer science and biology. After identifying disease-associated genes and proteins, ATx targets the root causes of a given condition. According to the scaleup, the process cuts the risks, costs, and time involved in developing treatments. The next big thing? It might be you… TNW Conference is here to support startups & scaleups to become the next big thing. Be part of the journey. Price increase on Friday. The new financing could push the benefits closer towards patients. ATx said the Series A funds will advance two frontrunner drugs: AT-001 and AT-004. AT-001 has proven particularly promising. The treatment focuses on dementia caused by harmful accumulations of protein. Its primary target is amyloid-induced angiopathy, a condition characterised by proteins amassing in the walls of the brain’s arteries. Taken orally, AT-001 disrupts and dissolves these harmful protein clusters. Consequently, the treatment could reduce the risks of dementia. ATx is confident of stalling the condition’s progression. The company also believes the drug could delay dementia’s onset — and even reverse its course. Ívar Hákonarson, the CEO and co-founder of ATx, said the treatment has “transformative potential.” “AT-001 offers hope for earlier intervention and even preventive use in individuals at high risk of developing dementia based on our biomarker signals,” he told TNW. Credit: ATxHákonarson co-founded ATx in 2015 as a spin-off from the US-based Center for Applied Genomics (CAG). Credit: ATx Changing the trajectory of dementia Tests on AT-001 are progressing rapidly. Last year, the European Medicines Agency (EMA) approved a new clinical trial that will probe the drug’s effects on HCCAA — a rare form of familial dementia. ATx also plans to launch a clinical trial for AT-004. The study aims to show the treatment is effective and safe for acne, before expanding into other inflammatory skin diseases. ATx expects the new funds to accelerate the research. A syndicate of international investors participated in the round. Among them is the European Commission’s EIC Fund, which supports companies developing disruptive tech. Svetoslava Georgieva, the chair of the EIC Fund Board, described the ATx financing as both an opportunity and a responsibility. “In Europe alone, dementia affects over 10 million people — placing immense strain on families, healthcare systems, and economies,” she said in a statement. “By providing an equity investment in Arctic Therapeutics, the EIC Fund is supporting groundbreaking preventive treatments that have the potential to change the trajectory of this crisis, improve quality of life, and alleviate the burden on healthcare infrastructure worldwide.” source

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Google has quietly released a major update to its popular artificial intelligence model, Gemini, which now explains its reasoning process, sets new performance records in mathematical and scientific tasks, and offers a free alternative to OpenAI’s premium services. The new Gemini 2.0 Flash Thinking model, released Tuesday in the Google AI Studio under the experimental designation “Exp-01-21,” has achieved a 73.3% score on the American Invitational Mathematics Examination (AIME) and 74.2% on the GPQA Diamond science benchmark. These results show clear improvements over earlier AI models and demonstrate Google’s increasing strength in advanced reasoning. “We’ve been pioneering these types of planning systems for over a decade, starting with programs like AlphaGo, and it is exciting to see the powerful combination of these ideas with the most capable foundation models,” wrote Demis Hassabis, CEO of Google DeepMind, in a post on X.com (formerly Twitter). Our latest update to our Gemini 2.0 Flash Thinking model (available here: https://t.co/Rr9DvqbUdO) scores 73.3% on AIME (math) & 74.2% on GPQA Diamond (science) benchmarks. Thanks for all your feedback, this represents super fast progress from our first release just this past… pic.twitter.com/cM1gNwBoTO — Demis Hassabis (@demishassabis) January 21, 2025 Gemini 2.0 Flash Thinking breaks records with million-token processing The model’s most striking feature is its ability to process up to one million tokens of text — five times more than OpenAI’s o1 Pro model — while maintaining faster response times. This expanded context window allows the model to analyze multiple research papers or extensive datasets simultaneously, a capability that could transform how researchers and analysts work with large volumes of information. “As a first experiment, I took various religious and philosophical texts and asked Gemini 2.0 Flash Thinking to weave them together, extracting novel and unique insights,” Dan Mac, an AI researcher who tested the model, said in a post on X.com. “It processed 970,000 tokens in total. The output is pretty incredible.” The release comes at a critical moment in the AI industry’s evolution. OpenAI recently announced its o3 model, which achieved an 87.7% score on the GPQA Diamond benchmark. However, Google’s decision to offer its model free during beta testing (with usage limits) could attract developers and enterprises seeking alternatives to OpenAI’s $200 monthly subscription. Benchmark results show Google’s latest Gemini 2.0 Flash Thinking model dramatically outperforming earlier versions across mathematics, science and reasoning tasks. (Credit: Google DeepMind) Google offers free Gemini 2.0 Flash Thinking with built-in code execution Jeff Dean, Chief Scientist at Google DeepMind, emphasized improvements in the model’s reliability: “We’re continuing to iterate, with higher reliability and reduced contradictions between the model’s thoughts and final answers,” he wrote. The model also includes native code execution capabilities, allowing developers to run and test code directly within the system. This feature, combined with improved contradiction safeguards, positions Gemini 2.0 Flash Thinking as a serious contender for both research and commercial applications. Industry analysts note that Google’s focus on explaining its reasoning process could help address growing concerns about AI transparency and reliability. Unlike traditional “black box” models, Gemini 2.0 Flash Thinking shows its work, making it easier for users to understand and verify its conclusions. We’re continuing to iterate, with higher reliability and reduced contradictions between the model’s thoughts and final answers. Check it out as gemini-2.0-flash-thinking-exp-01-21 at https://t.co/sw0jY6k74m — Jeff Dean (@JeffDean) January 21, 2025 AI transparency becomes the new battleground as Google challenges OpenAI The model has already claimed the top spot on the Chatbot Arena leaderboard, a prominent benchmark for AI performance, leading in categories including hard prompts, coding, and creative writing. However, questions remain about the model’s real-world performance and limitations. While benchmark scores provide valuable metrics, they don’t always translate directly to practical applications. Google’s challenge will be convincing enterprise customers that its free offering can match or exceed the capabilities of premium alternatives. As the AI arms race intensifies, Google’s latest release suggests a shift in strategy: combining advanced capabilities with accessibility. Whether this approach will help close the gap with OpenAI remains to be seen, but it certainly gives technical decision makers a compelling reason to reconsider their AI partnerships. For now, one thing is clear: the era of AI that can show its work has arrived, and it’s available to anyone with a Google account. source

The mobile application market is projected at an annual compound growth rate (CAGR) of 14.3% between now and 2030, and businesses are capitalizing by developing mobile applications for customers, business partners, and internal use. In large part, the mobile app market is being driven by the explosive growth of mobile devices, which over 60% of the world’s population use. Not all of this use is confined to social media, emails, phone calls, and texts. Accordingly, businesses have become involved with launching retail websites for mobile devices, as well as transactional engines for mobile payment processing, e-commerce, banking and booking systems for use in a variety of smart mobile devices. In the process, the key for IT has been the integration of these new mobile applications with enterprise systems. How do you ensure that a mobile app is tightly integrated into your existing business processes and your IT base, and how do you ensure that it will perform consistently well every time it is used? Is your security policy across mobile devices as robust as it is across other enterprise assets, such as mainframes, networks and servers? Does the user interface across all mobile devices navigate equally well and with a certain degree of consistency, no matter which device is used? Related:Securing a Better Salary: Tips for IT Pros In most cases, IT departments (and users and customers) will say that total mobile device integration is still a work in progress. The Role of Mobile App Integration In the past, the integration of mobile applications with other IT infrastructure was more or less confined to the IT assets that the mobile app minimally needed to perform its functions. If the app was there for placing an online order, access to the enterprise order entry, inventory and fulfillment systems was needed, but maybe nothing else for the first installation. If the app was designed for a warehouse worker to operate a series of robots to pick and place items in a warehouse, it was specifically developed just for that, and on first installment, it might not have been integrated into inventory and warehouse management systems. However, now that tech companies are placing their R&D emphasis on smart phones and devices, IT needs to formulate a more inclusive integration strategy for mobile applications that  these apps more “complete” when they launch. The Elements of Mobile App Integration To achieve total integration with the rest of the enterprise IT portfolio, and possibly with third-party services, a mobile app must do the following: Related:Untangling Enterprise Reliance on Legacy Systems Attain seamless data exchange across all systems, along with having the ability to invoke and use system-level infrastructure components such as storage or system-level routines to do its work. Use application programming interfaces (APIs) so it can access other IT and/or vendor systems. Conform to the same security and governance standards that other IT assets are subject to. Provide users and customers with a simple and (as much as possible) uniform graphical user interface (GUI). Be right-fitted into existing business and system workflows. This isn’t just good IT. It also makes major contributions to user productivity and customer satisfaction. Workflow Integration In late 2024, a health insurance company unveiled an automated online process for new customer registration. Unfortunately, the new app didn’t include all data elements needed for registration, and it actually froze in process. Users ended up calling the company and enduring long wait times until they could complete their registrations with a human agent. This was a case of workflow integration failure, because critical ingredients required for registration had been left out of the online mobile app. How did this happen? The project might have been rushed through to meet a deadline or signed off as a first (albeit incomplete) version of an app that would be later enhanced. Or, possibly, QA might have been skipped. But to an experienced IT “eye,” the app was clearly missing data, which suggested that integration with other enterprise systems, or data transfers via API with supporting vendor systems, had been missed. Related:How to Persuade an AI-Reluctant Board to Embrace Critical Change The app’s process flow also was a “miss” because if the project team had tested the mobile app’s process flow against the business workflow, they would have seen (like customers did) that key data elements were missing, and that the workflow didn’t work. The project team should also have verified that security and governance standards had been met, and that the mobile app user experience was consistent, whether the customer was using an iPhone or an Android. Summary Statista says that the mobile application market will reach $756 billion by 2027. In the US, 47% of mobile apps are being used for retail transactions, and another 19% are serving as portals, whether for customers, business partners or employees. There is virtually no business that isn’t developing mobile apps today for its customers, business partners and/or employees, but what has lagged is the same level of discipline over mobile app development that IT expects for traditional enterprise app development. Central to this is mobile application integration. It’s no longer acceptable to let an app “fly” with just the basics, but with many functions and data elements still missing. It’s time for top-to-bottom mobile app integration, whether that integration requires complete data, a uniform user experience across all devices, or something else. source

Any Linux server distribution is a very powerful server that performs above and beyond what your business might need. Whatever task you throw at the server, it will be ready. And, if it isn’t ready out of the box, you can make it so. If you aren’t sure about SFTP, it is the FTP service built into Secure Shell (SSH), which allows users to securely push and pull files to and from the server, using SSH. I’m going to walk you through the process of setting up an SFTP server. I’ll demonstrate by creating a single user that is limited to only SFTP logins. Once you know how to do this, you can create as many users as you need. This process will work on any Linux distribution. Let’s make it work. SEE: Troubleshooting Linux: An Admin’s Guide (TechRepublic Premium) What you’ll need You’ll need access to an account with admin rights. Once you’ve procured that access, it’s time to make this work. SFTP Directory The first thing we must do is create a directory that will house our FTP data. Open up a terminal window, su to the root user (type su and then, when prompted, type the root user password), and then issue the following two commands: mkdir -p /datachmod 701 /data SEE: How to Add an SSH Fingerprint to Your known_hosts File in Linux (TechRepublic) Create the SFTP group and user Now we’re going to create a special group for SFTP users. This is done with the following command: groupadd sftp_users Now we’re going to create a special user that doesn’t have regular login privileges, but does belong to our newly created sftp_users group. What you call that user is up to you. The command for this is: useradd -g sftp_users -d /upload -s /sbin/nologin USERNAME Where USERNAME is the name of the user. Next, give the new user a password. This password will be the password the new users use to log in with the sftp command. To set up the password, issue the command: passwd USERNAME Where USERNAME is the name of the user created above. SEE: How to Start, Stop, and Restart Services in Linux (TechRepublic) Create the new user SFTP directory Now we’re going to create an upload directory, specific to the new user, and then give the directory the proper permissions. This is handled with the following commands: mkdir -p /data/USERNAME/uploadchown -R root:sftp_users /data/USERNAMEchown -R USERNAME:sftp_users /data/USERNAME/upload Where USERNAME is the name of the new user you created above. Configure sshd Open up the SSH daemon configuration file with the command: nano /etc/ssh/sshd_config At the bottom of that file, add the following: Match Group sftp_usersChrootDirectory /data/%uForceCommand internal-sftp Save and close that file. Restart SSH with the command: systemctl restart sshd SEE: 5 Best Linux CentOS Replacement Options & Alternatives (TechRepublic) Logging in You’re all set to log in. From another machine on your network that has SSH installed, open up a terminal window and issue the command: sftp USERNAME@SERVER_IP Where USERNAME is the name of our new user and SERVER_IP is the IP address of our SFTP server. You will be prompted for USERNAME’s password. Once you successfully authenticate, you will be greeted with the sftp prompt. Type pwd to check the working path and you should see /upload as depicted in the image below. After you have successfully completed authentication, you will see the sftp prompt. Image: Jack Wallen A simple solution That’s all there is to setting up an SFTP server on Linux. For any company looking to offer staff and clients a simple, secure means of uploading and downloading files, this is a not only a great solution but also very budget friendly one. Get your SFTP server up and running with zero cost and zero headache. This article was originally published in September 2019. It was updated by Antony Peyton in January 2025. source

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Agentic AI is the latest big trend in generative AI, but what comes after that? While full artificial general intelligence (AGI) is likely still some time in the future, there might well be an intermediate step with an approach known as ambient agents. LangChain, the agentic AI pioneer, introduced the term “ambient agents” on January 14. The technology that LangChain develops includes its eponymous open source LangChain framework that enables organizations to chain different large language models (LLMs) together to get a result. LangChain Inc. raised $24 million in funding in February 2024. The company also has a series of commercial products including LangSmith for LLM Ops. With a traditional AI interface, users typically interact with an LLM via text prompts to initiate an action. Agentic AI generally refers to LLM-powered systems that take actions on the user’s behalf. The concept of ambient agents takes that paradigm a step further. What are ambient agents? Ambient agents are AI systems that run in the background, continuously monitoring event streams and then triggered to act when appropriate, according to pre-set instructions and user intent. While the term “ambient agents” is new, the concept of ambient intelligence, where AI is always listening, is not. Amazon refers to its Alexa personal assistant technology as enabling ambient intelligence. The goal of ambient agents is to automate repetitive tasks and scale the user’s capabilities by having multiple agents running persistently, rather than the human user having to call them up and interact with each one, one-on-one. This allows the user to focus on higher-level tasks while the agents handle routine work. To help prove out and advance the concept of ambient agents, LangChain has developed a series of initial use cases, one that monitors emails, the other for social media, to help users manage and respond when needed.  “I think agents in general are powerful and exciting and cool,” Harrison Chase, cofounder and CEO of LangChain, told VentureBeat. “Ambient agents are way more powerful if there’s a bunch of them doing things in the background, you can just scale yourself way more.” The tech leverages many open-source solutions, and LangChain did not indicate yet how much it would charge for use of any new tools. How ambient agents work to improve AI usability Like many great technology innovations, the original motivation for ambient agents wasn’t to create a new paradigm, but rather to solve a real problem. For Chase, the problem is one that is all too familiar for many of us: email inbox overload. Chase began his journey to create ambient agents to solve email challenges. Six months ago he started building an ambient agent for his own email. Chase explained that the email assistant categorizes his emails, handling the triage process automatically. He no longer has to manually sort through his inbox, as the agent takes care of it. Through his own use of the agent inbox over an extended period, Chase was able to refine and improve its capabilities. He noted that it started off imperfect, but by using it regularly and addressing the pain points, he was able to enhance the agent’s performance. To be clear, the email assistant isn’t some kind of simplistic rules-based system for sorting email. It’s a system that actually understands his email and helps him to decide how to manage it. The ambient agent architecture for the email assistant use case The architecture of Chase’s email assistant is quite complex, involving multiple components and language models.  “It starts off with a triage step that’s kind of like an LLM and a pretty complicated prompt and some few short examples which are retrieved semantically from a vector database,” Chase explained. “Then, if it’s determined that it should try to respond, it goes to a drafting agent.” Chase further explained that the drafting agent has access to additional tools, including a sub-agent specifically for interacting with the calendar: “There’s an agent that I have specifically for interacting with the calendar, because actually LLMs kind of suck at dates,” Chase said. “So I had to have a dedicated agent just to interact with the calendar.” After the draft response is generated, Chase said there’s an additional LLM call that rewrites the response to ensure the correct tone and formatting. “I found that having the LLM try to call all these tools and construct an email and then also write in the correct tone was really tricky, so I have a step explicitly for tone,” Chase said. The agent inbox as a way to control and monitor agents A key part of the ambient agent experience Is having control and visibility into what the agents are doing. Chase noted that in an initial implementation, he just had agents message via Slack, but that quickly became unwieldy. Instead, LangChain designed a new user interface, the agent inbox, specifically for interacting with ambient agents. Screenshot of LangChain agent box. Credit: VentureBeat The system displays all open lines of communication between users and agents and makes it easy to track outstanding actions. How to build an ambient agent LangChain first and foremost is a tool for developers and it’s going to be a tool to help build and deploy ambient agents now too. Any developer can use the open-source LangChain technology to build an ambient agent, though additional tools can simplify the process. Chase explained that the agent inbox he built is in some respect a view on top of the LangGraph platform. LangGraph is an open-source framework for building agents that provides the infrastructure for operating long-running background jobs. On top of that, LangChain is using its commercial LangSmith platform, which provides observability and evaluation for agents. This helps developers put agents into production with the necessary monitoring and evaluation tools to ensure they are performing as expected. Ambient agents: A step toward using generalized intelligence Chase is optimistic that the concept of