Tata Communications has announced the launch of its Unified/ Single-Vendor Hosted Secure Access Service Edge (SASE) for global enterprises.
Launched in partnership with Versa Networks, a leader in AI-powered Unified SASE, Tata Communications Hosted SASE, converges software-defined wide area networks (SD-WAN) and secure service edge (SSE) capabilities in a single pass technology enabling future ready businesses to fully harness the power and potential of cloud-based environments through exceptional performance, zero-trust security, ease of use, and cost effectiveness.
Hosted and managed end-to-end by Tata Communications, the solution offers secure, scalable, and agile deployment. The company’s cross domain expertise across network, security and cloud, delivers a seamless operational management and integration with existing systems for enterprises, ensuring robust support throughout their journey.
As enterprises increasingly adopt hybrid working, SD-WAN and a digital-first approach, their distributed network architecture increases vulnerability to cyberattacks, and hence the need for robust SSE solutions.
A study commissioned by Tata Communications with Omdia identified that secure remote working was the top driver (49%) for adopting SASE solutions in global businesses, followed closely by simplified and integrated security models (43%). Furthermore, when implementing SASE, nearly half of businesses cited siloed security and networks teams as a key challenge.
Tata Communications Hosted SASE is uniquely positioned to address these challenges. The company is harnessing its globally distributed network for delivering Hosted SASE ensuring carrier grade connectivity and superior performance. It also offers advanced detection and real-time protection via a cyber threat intelligence platform that generates insights by aggregating data from Tata Communications’ network and other leading industry sources.
“Our customers operate in a hyperconnected environment, so it is vital that they are able to access data anytime anywhere without compromising on security or user experience. Our Hosted SASE solution powers global businesses with secure communication and collaboration weaving all of their data and applications into a single digital fabric that enables end-to-end control and visibility,” Srinivasan CR, executive vice president-cloud and cybersecurity services & chief digital officer, Tata Communications, said.
Tata Communications Hosted SASE’s single pass technology ensures unified visibility and control of network traffic along with actionable insights to optimize network performance.
This helps enterprises to avoid complexities and delays in managing an ever-growing stack of point solutions. Furthermore, they can also improve their return on investment — with Tata Communications Hosted SASE, the cost of ownership is estimated to be nearly 40% lower than deploying point solutions.
Pure Storage, a leader in advanced data storage technologies, has announced significant advancements to its platform designed to revolutionise data centres in the face of AI’s rapid evolution and the increasing threat of ransomware.
Unveiled at the Accelerate conference, these innovations promise to redefine how IT and business leaders manage and secure their data infrastructures.
With AI driving major transformations in business, cyber-criminals are also exploiting AI to enhance the scale and impact of their attacks, particularly ransomware.
Current data centre infrastructures often struggle to keep pace with these rapid changes, lacking the flexibility and resilience needed for effective data protection and recovery. Pure Storage addresses these challenges with a comprehensive, agile, and resilient data storage platform.
Evergreen//One for AI, one of Pure Storage’s latest offerings, is designed specifically for AI workloads. This service guarantees storage performance for GPUs, essential for training, inference, and HPC tasks.
It allows data centres to dynamically scale capacity and performance without the complexity of traditional infrastructure planning, ensuring efficient and cost-effective operations.
Pure Fusion integrates advanced automation capabilities, enabling seamless optimisation of storage pools across structured and unstructured data environments, both on-premises and in the cloud. This innovation is embedded within the Purity operating environment, ensuring continuous improvement through non-disruptive upgrades. This level of automation simplifies data management and enhances operational efficiency.
Pure Storage is set to achieve certification for NVIDIA DGX SuperPOD by the end of 2024, building on its existing collaboration with NVIDIA. This certification will streamline the deployment of AI-ready infrastructure in data centres, enhancing performance for large-scale AI applications. This partnership underscores Pure Storage’s commitment to delivering cutting-edge solutions for AI integration.
A recent survey of 1,500 global CIOs and decision makers, commissioned by Pure Storage, revealed that 98% believe their data infrastructure must improve to support AI initiatives. Pure Storage’s new platform capabilities address this need by delivering scalable, reliable, and energy-efficient solutions that consume up to 85% less energy than traditional all-flash storage systems. This not only supports AI initiatives but also helps in reducing the environmental footprint of data centres.
“Pure is redefining enterprise storage with a unified platform that meets the diverse needs of data centres, from AI integration to cyber resilience,” said Charles Giancarlo, Chairman and CEO of Pure Storage. “Our innovations provide unmatched consistency, resilience, and SLA-guaranteed services, reducing costs and uncertainty in today’s dynamic business environment.”
Another innovation is the industry-first generative AI copilot for storage. This AI-driven tool represents a breakthrough in data management, utilising natural language processing to assist storage teams in investigating performance issues and preempting security incidents. Leveraging insights from thousands of Pure Storage customers, this copilot guides users through complex data management tasks with ease, improving both performance and security.
Pure Storage has also expanded its Cyber Recovery and Resilience SLA, offering a comprehensive disaster recovery solution that includes tailored recovery plans, clean service infrastructure delivery, onsite installation, and ongoing security assessments. This SLA ensures that data centres can quickly restore operations after any disruptive event, providing a robust safety net against cyber threats.
In addition, new enhancements to anomaly detection capabilities enable data centres to identify and mitigate threats such as ransomware and malicious activities through advanced machine learning models. This proactive approach minimises operational disruptions and ensures rapid recovery from security incidents, bolstering overall data centre security.
“We’re excited to bring these new capabilities to our customers in India, helping them leverage AI and enhance their cyber resilience,” said Ramanujam Komanduri, Country Manager, India, Pure Storage.
These advancements position Pure Storage at the forefront of data centre innovation, enabling businesses to navigate the challenges of AI and cybersecurity with confidence and efficiency.
Texas-based leading travel industry software and technology provider, Sabre, has been leveraging AI and ML for a while now. In a recent interaction with AIM, Sandeep Bhasin, VP (software engineering) at Sabre, said that internally, the company has introduced generative AI tools to approximately 800 software engineers, significantly enhancing productivity and innovation.
By leveraging generative AI, the company aims to improve the efficiency of its development processes and bring new products to market faster.
Apart from internally experimenting with AI, it recently unveiled SabreMosaic. This AI-powered modular platform shifts from the traditional PNR system to a modern offer and order approach and enables airlines to offer personalised and dynamic retail experiences.
Traditional airline processes relied heavily on the PNR to manage traveller information, but this system has struggled to evolve with the expansion of airline product offerings. The rise of modern retailers like Amazon has shifted traveller expectations towards personalised experiences.
“Travellers now expect the same level of personalisation from their travel providers as they have come to expect in other B2C retailing spaces,” added Bhasin.
This shift is driving airlines to adopt modern retailing platforms like SabreMosaic, which supports both PNR and Offer-Order systems. Offer-Order systems optimise and personalise travel offers, allowing airlines to sell a variety of products beyond just flight tickets.
“What excites me is how this dual support is crucial as airlines transition from being mere suppliers of seat inventory to modern retailers of diverse travel content,” he added.
The product is driven by the company’s suite of AI/ML-powered solutions called Sabre Travel AI, developed using Google Cloud’s Vertex AI platform. The team also uses other models like multi-cloud data warehouse Big Query for its data lake.
Back in 2022, Sabre announced a 10-year-long partnership with Google to leverage its capabilities for new innovation. The former’s extensive travel data and this partnership will enable it to provide effective, data-driven recommendations.
Talking about the same, Bhasin said, “Our wealth of travel data gives us the advantage to leverage the power of data, often referred to as the new oil, to drive our analytical models.” This capability allows Sabre to offer real-time interaction and decision-making on a global scale.
The real-time capabilities of the model is another differentiator making interactions faster and instant.
Can AI Help in the Cancellation Crisis?
Even though the Indian aviation sector has seen remarkable growth over the past few years, with domestic air passenger traffic increasing by 13% annually to about 15.4 crore in 2023-24, major airline chains like IndiGo, Vistara, Air India, Akasa Air, and SpiceJet have faced challenges in maintaining flight schedules. As of the January-March 2024 period, flight cancellations and delays rose by 34%.
Given this current situation, where flight cancellations are more common than ever, AI and ML can play a crucial role in mitigating these disruptions. According to Bhasin, re-accommodation logic can manage flight disruptions more efficiently.
As Bhasin explained, “As airlines move further towards modern retailing, it will be important that a travellers’ personalised ‘bundle’ of products is kept together as an offer so that, even if disruption happens, the passenger still receives their expected ancillaries or experiences.”
Additionally, robust optimisation strategies and technology are essential for creating schedules and routes that are less prone to disruptions.
Aviation companies are already using AI, especially generative AI for customer experience. For example, Air India introduced AI.g, a virtual travel assistant, powered by ChatGPT on WhatsApp. Even IndiGo launched an AI chatbot called 6Eskai. Both the models are built on OpenAI’s GPT-4.
India as a Market
“The India centre plays a crucial role. In fact, a lot of our recent technology transformation initiatives, including our move to Google Cloud, were run out of the India centre,” commented Bhasin. This includes major initiatives like moving from mainframe systems to open systems and transitioning to cloud infrastructure.
The company has major GCCs in Krakow, Bengaluru, and Montevideo. In India, Air India is one of its largest customers along with various travel agencies and hotels. The Bengaluru Global Capability Center (GCC) plays a crucial role in driving technological transformation.
The Bengaluru GCC has been instrumental in these transformations, developing industry-leading solutions for the travel business and providing a strong IT backbone to global operations.
Bhasin highlighted, “Several products from our retail intelligence suite, along with the leadership team behind it, including our MLOps practice, are also based out of our Bengaluru GCC.”
The company’s retail intelligence suite includes AI and ML-powered products like Air Price IQ and Ancillary IQ, which offer personalised and optimised air prices and ancillary services. For example, Air Serbia and Chile-based LATAM air services have co-innovated with Sabre to bring these products to market, resulting in substantial revenue increases.
With Air Price IQ, our customers can expect up to a 3% revenue increase in flight revenue. With Ancillary IQ, it could be up to 10% of the overall ancillary revenue.
The Bengaluru GCC has been instrumental in these transformations, developing industry-leading solutions for the travel business and providing a strong IT backbone to global operations.
Several products from the Retail Intelligence suite, along with the leadership team behind it, including our MLOps practice, are also based out of the Bengaluru GCC. The company is currently in talks with these customers to implement Sabre Travel AI solutions.
“India is one of the most dynamic, complex, and fast-growing markets in the world right now, and it’s one of our key markets for 2024 and beyond. And our team in India is critical to our tech transformation and innovation efforts,” concluded Bhasin.
Hewlett Packard Enterprise (HPE) has teamed up with Nvidia to offer what they are touting as an integrated "turnkey" solution for organizations looking to adopt generative artificial intelligence (GenAI), but are put off by the complexities of developing and managing such workloads.
Dubbed Nvidia AI Computing by HPE, the product and service portfolio encompasses co-developed AI applications and will see both companies jointly pitch and deliver solutions to customers. They will do so alongside channel partners that include Deloitte, Infosys, and Wipro.
Also: AI's employment impact: 86% of workers fear job losses, but here's some good news
The expansion of the HPE-Nvidia partnership, which has spanned decades, was announced during HPE president and CEO Antonio Neri's keynote at HPE Discover 2024, held at the Sphere in Las Vegas this week. He was joined on stage by Nvidia's founder and CEO Jensen Huang.
Neri noted that GenAI holds significant transformative power, but the complexities of fragmented AI technology come with too many risks that hinder large-scale business adoption. Rushing in to adopt can be costly, especially for a company's most priced asset — its data, he said.
Huang added that there are three key components in AI, namely, large language models (LLMs), the computing resources to process these models and data. Therefore, companies will need a computing stack, a model stack, and a data stack. Each of these is complex to deploy and manage, he said.
The HPE-Nvidia partnership has worked to productize these models, tapping Nvidia's AI Enterprise software platform including Nvidia NIM inference microservices, and HPE AI Essentials software, which provides curated AI and data foundation tools alongside a centralized control pane.
The "turnkey" solution will allow organizations that do not have the time or expertise to bring together all the capabilities, including training models, to focus their resources instead on developing new AI use cases, Neri said.
Key to this is the HPE Private Cloud AI, he said, which offers an integrated AI stack that comprises Nvidia Spectrum-X Ethernet networking, HPE GreenLake for file storage, and HPE ProLiant servers optimized to support Nvidia's L40S, H100 NVL Tensor Core GPUs, and GH200 NVL2 platform.
Also: Latest AI training benchmarks show Nvidia has no competition
AI requires a hybrid cloud by design to deliver GenAI effectively and through the full AI lifecycle, Neri said, echoing what he said in March at Nvidia GTC. "From training and tuning models on-premises, in a colocation facility or the public cloud, to inferencing at the edge, AI is a hybrid cloud workload," he said.
With the integrated HPE-Nvidia offering, Neri is pitching that users can get set up on their AI deployment in just three clicks and 24 seconds.
Huang said: "GenAI and accelerated computing are fueling a fundamental transformation as every industry races to join the industrial revolution. Never before have Nvidia and HPE integrated our technologies so deeply — combining the entire Nvidia AI computing stack along with HPE's private cloud technology."
Removing the complexities and disconnect
The joint solution brings together technologies and teams that are not necessarily integrated within organizations, said Joseph Yang, HPE's Asia-Pacific and India general manager of HPC and AI.
AI teams (in companies that have them) typically run independently from the IT teams and may not even report to IT, said Yang in an interview with ZDNET on the sidelines of HPE Discover. They know how to build and train AI models, while IT teams are familiar with cloud architectures that host general-purpose workloads and may not understand AI infrastructures.
Also: Generative AI's biggest challenge is showing the ROI — here's why
There is a disconnect between the two, he said, noting that AI and cloud infrastructures are distinctly different. Cloud workloads, for instance, tend to be small, with one server able to host several virtual machines. In comparison, AI inferencing workloads are large, and running AI models requires significantly larger infrastructures, making these architectures complicated to manage.
IT teams also face growing pressure from management to adopt AI, further adding to the pressure and complexity of deploying GenAI, Yang said.
He added that organizations must decide what architecture they need to move forward with their AI plans, as their existing hardware infrastructure is a hodgepodge of servers that may be obsolete. And because they may not have invested in a private cloud or server farm to run AI workloads, they face limitations on what they can do since their existing environment is not scalable.
"Enterprises will need the right computing infrastructure and capabilities that enable them to accelerate innovation while minimizing complexities and risks associated with GenAI," Yang said. "The Nvidia AI Computing by HPE portfolio will empower enterprises to accelerate time to value with GenAI to drive new opportunities and growth."
Also: AI skills or AI-enhanced skills? What employers need could depend on you
Neri further noted that the private cloud deployment also will address concerns organizations may have about data security and sovereignty.
He added that HPE observes all local regulations and compliance requirements, so AI principles and policies will be applied according to local market needs.
According to HPE, the private cloud AI offering provides support for inference, fine-tuning, and RAG (retrieval-augmented generation) AI workloads that tap proprietary data, as well as controls for data privacy, security, and compliance. It also offers cloud ITOps and AIOps capabilities.
Powered by HPE GreenLake cloud services, the private cloud AI offering will allow businesses to automate and orchestrate endpoints, workloads, and data across hybrid environments.
Also: How my 4 favorite AI tools help me get more done at work
HPE Private Cloud AI is slated for general availability in the fall, alongside HPE ProLiant DL380a Gen12 server with Nvidia H200 NVL Tensor Core GPUs and HPE ProLiant DL384 Gen12 server with dual Nvidia GH200 NVL2.
HPE Cray XD670 server with Nvidia H200 NVL is scheduled for general availability in the summer.
Eileen Yu reported for ZDNET from HPE Discover 2024 in Las Vegas, at the invitation of Hewlett Packard Enterprise.
Some worry that artificial intelligence will destroy many existing jobs. That's the subject of another article. What's happening on the ground, however, is that AI may be at the core of new roles, especially with organizations pouring increasing amounts of money into the technology, with hopes that it will deliver.
It's hard to predict what job titles will emerge over the next couple of years. After all, nobody could have conceived of titles such as "cloud engineer" or "digital sherpa" a few years back.
Also: Tech giants hatch a plan for AI job losses: Reskill 95 million in 10 years
We know that data scientists and Python developers are needed to build and maintain AI. Andy Thurai, principal analyst with Constellation Research, suggests we'll see new types of titles in the next few years as well. These titles may sound whimsical now (and Andy meant them to be), but the underlying roles will be needed for vital tasks in budding AI-driven businesses.
Prompt Whisperer: Coaxes the best output out of AI models by crafting clever prompts
Hallucination Wrangler: Tames the AI model when it starts generating nonsensical or off-topic content
Data DJ: Mixes and matches datasets to create the perfect training recipe for the AI model
Bias Buster: Responsible for identifying and mitigating biases in AI algorithms
Synthetic Sommelier: Curates and recommends the best AI-generated content for specific purposes
Digital Puppet Master: Designs and controls AI characters for various applications
Algorithm Alchemist: Experiments with different AI techniques to create innovative solutions
Neural Network Nanny: Nurtures and trains AI models to reach their full potential
Reality Check Officer: Verifies the accuracy and authenticity of AI-generated content
Chief Creative Catalyst: Oversees and inspires a team of AI-powered creatives
Kill Switch Engineer (or AI Tamer): Starts pulling cables in case AI is trying to take control (this one is the most realistic job!)
Across the business technology landscape, industry movers and shakers are seeing demand growing for a range of new roles to tame the AI beast. Maybe not with Thurai's suggested titles, but charged with the same tasks.
At the leadership level, for example, Anurag Gupta, global head of solutions consulting at Revature, sees AI-related leadership roles as "critical for setting the vision, standards, and roadmap for generative AI projects."
Also: What is a Chief AI Officer, and how do you become one?
This may include chief AI officers, Gupta told ZDNET. AI product managers are also coming to the fore, "playing a critical role in helping design, develop, and manage AI-powered products and services." Also emerging: "The need for generative AI engineers continues to rise as organizations apply new techniques to develop, deploy, and maintain AI solutions that solve real-world problems."
The common thread for many of AI's new roles can be considered part of the realm of "AI transformation," Sania Khan, Eightfold AI's chief economist and head of insights, told ZDNET. These roles are becoming part of "teams entrusted with the critical task of selecting the right AI tools for each function and formulating workforce strategies to ensure agility, productivity, and employee engagement."
Preparing to assume such roles requires a change in direction in learning and preparing. Hopefully, this includes being part of an organization that encourages continuous learning. "Skills-based organizations that consistently assess in-demand skills needed to future-proof the workforce, invest in upskilling/reskilling workers, and recalibrate roles will remain ahead of the curve," Khan said.
Unfortunately, many organizations won't support such learning — and even schools and universities can't keep up. "Finding formal training or relevant qualifications through traditional channels may prove challenging," Bernhard Gademann, president of the Institut auf dem Rosenberg, told ZDNET.
Also: More than money, open-source pros want these 2 things from their next jobs
"We suggest that individuals embark on a self-directed learning journey, exploring and applying AI in various scenarios and contexts," Gademann said. "With the abundance of information published daily, there are ample opportunities to learn and be inspired. However, this path demands a highly self-motivated mindset, which — clearly — is another important future skill."
With technology changing so fast, the time it takes for a technology skill to become obsolete is now less than three years. Gupta urges getting involved with "hands-on or project-based approaches that offer the opportunity to work on real-world projects and scenarios to master and acquire new skills." Such skills not only involve generative AI, but also security and cloud, along with foundational skills "such as core programming, no code, low code, data science, business analysis, and QA testing."
At the Apple WWDC 24, the company announced Apple Iintelligence. Undoubtedly, the key focus was privacy and how AI can be used on your phone to actually help you. But Apple left a hidden gem to be discovered by developers.
It turns out that you can use Apple’s own open source machine learning library, MLX, to fuse your Apple devices together to create one giant AI cluster. This way you can locally run large AI models without internet.
A user already shared his experience fusing 2 MacBook, 2 iPhone 15 Pro, and one iPad to run Llama 3 8b instruct 4 bit model:
Connecting a bunch of iPhones, iPads and MacBooks together over a local network to make one big GPU. Uses Apple’s open source ML library, MLX https://t.co/Ran48fwMNB
— Alex Cheema – e/acc (@ac_crypto) June 13, 2024
But is it beyond Apple-only devices
The developer who tested MLX with multiple Apple devices mentioned that as long as you have a computer with decent computational power, you can use any computer and it does not have to be Apple only.
it can be stacked to run large models with only once condition that all the devices has to be under the same network.
It is made possible because of the MLX is opensource and can easily be installed as a Python package.
This opens a new possibility for for developers and tech users. For example, complex tasks such as large-scale text generation, image synthesis with Stable Diffusion, and speech recognition with models like OpenAI’s Whisper can be executed more efficiently.
Developers can experiment with advanced AI models without the need for expensive cloud services, making AI research and application development more accessible.
Apart from NVIDIA becoming the world’s most valuable company, its chief Jensen Huang answers what new applications in AI he is the most excited about going forward.
Bets Big on Proactive Customer Service
Jensen believes that the future of customer service is going to change significantly.
“The number one most impactful AI application will probably be customer service,” said Huang, explaining that the important thing about the chatbot and the customer service is the data flywheel that can capture all the conversation and engagement and create more data.
“Currently, we’re seeing data growing about 10x every five years. I would not be surprised to see data growing 100x every five years because of customer service,” he said, adding that it will help companies collect more data and insights to extract better intelligence and provide better service.
He further highlighted that it might help to reach a time when companies are able to contact the customer and proactively solve a problem even before it arises. “Just like preemptive maintenance, we’re going to have proactive customer support,” Huang said while earlier mentioning that every company’s business data is its gold mine.
GenAI is already changing the game for customer service. Today, many companies are leveraging it to supercharge their customer support.
Recently, Bland AI put up a cool billboard advertising promoting its AI agent that can handle all sorts of phone calls for businesses in any voice, and it created a buzz.
This is one cool billboard advertising promoting AI agent. Calling that number will connect u to a live conversation with an AI bot powered by @usebland. pic.twitter.com/A9tCLFU5dP
— Alvin Foo (@alvinfoo) April 25, 2024
Automation Anywhere, a leader in AI-driven automation, also launched new AI Agents that can slash the time of process tasks from hours to minutes, increasing business impact up to tenfold in areas like customer service.
Velocity, a top Indian cash flow-based financing platform launched Vani AI, India’s first AI-based interactive calling solution for financial institutions to help reduce operational costs by 20-30% while enhancing customer experience.
Fractal Analytics, a leading AI solutions provider for Fortune 500 companies, effectively reduced call handling time by up to 15% using its latest innovation, dubbed Knowledge Assist, on AWS.
During a six-month pilot program, nearly 500 knowledge workers in contact centres adopted Knowledge Assist, handling hundreds of thousands of queries monthly and managing complex data from over 10,000 documents across pdf, doc, and ppt formats. The pilot showed a 10-15% reduction in average data retrieval time and a 30% call deflection rate due to self-service capabilities.
Generative AI for Everyone
NVIDIA’s chief said that GenAI is everywhere and we’re at the beginning of a new industrial revolution. Instead of generating electricity, we’re generating intelligence.
“Recently, using GenAI, we made it possible to make regional weather predictions down to a couple of kilometres. It would have taken a supercomputer about 10,000 times more capability to predict weather down to a kilometre,” he added, saying that he’s also excited about the fact that GenAI is being used to generate chemicals, proteins, and even physics or physical AI.
Huang believes GenAI can help enhance logistics, insurance, and also keep people out of harm’s way. From physical things, biological things, and GenAI for 3D graphics and digital twins, to creating virtual worlds for video games, every industry is involved in GenAI according to him and those that are not, are just not paying attention.
When asked about his thoughts on how enterprises can make AI that’s more sustainable, Huang said that sustainability has a lot to do with energy and we don’t need to put AI training data centres where the energy grid is already challenged.
“The Earth has a lot more energy, it’s just in the wrong places. We can capture that excess energy, compress it into an AI model, and then bring these AI models back to the society where we could use it,” he said, adding that AI doesn’t care where it went to school.
The Future is Small
Finally, Huang added that while today the computing experience is retrieval-based, in the future, it’s going to be more contextual, more generative, and right there on the device running a small language model. This will dramatically reduce the amount of internet traffic.
“It’ll be much more generative with some retrieval to augment. The balance of computation will be dramatically shifted towards immediate generation. This way of computing is going to save a ton of energy and it’s very sensible,” he said.
Similarly, Microsoft and Meta also made announcements focused on small language models.
Huang highlighted that the big idea about the future as working with AIs is prompting, adding, “We’re going to have so many more interesting questions because we’re going to get a lot of answers very quickly.”
When asked how to best help customers and organisations get started today with GenAI, Huang said that users can leverage platforms like Databricks’ Data Intelligence Platform (DIP) and NVIDIA NIMs.
NIMs (NVIDIA Inference Microservices) are containerized AI microservices designed to accelerate the deployment of GenAI models across various infrastructures.
It simplifies the creation of GenAI applications such as copilots and chatbots, by providing scalable deployment, advanced language model support, flexible integration, and enterprise-grade security, thereby enabling developers to build powerful AI applications quickly.
“Go get yourself a NIM on DIP,” he said, encouraging people to engage with AI.
“Whatever you do, just start and engage! GenAI is one of those things you can’t learn by watching or reading about. You just learn by doing. It is growing exponentially and you don’t want to wait and observe an exponential trend because in a couple of years you’ll be left so far behind. So, just get on the train, enjoy it and learn along the way!” suggested the NVIDIA chief.
At SUSECon in Berlin, SUSE, a global Linux and cloud-native software leader, announced significant enhancements across its entire Linux distribution family. These new capabilities focus on providing faster time-to-value and reduced operational costs, emphasizing the importance of choice in today's complex IT landscape.
SUSE Linux Enterprise Server (SLES) 15 Service Pack (SP) 6 is at the heart of these upgrades. This update future-proofs IT workloads with a new Long Term Service (LTS) Pack Support Core. How long is long-term? Would you believe 19 years? This gives SLES the longest-term support period in the enterprise Linux market. Even Ubuntu, for which Canonical recently extended its LTS to 12 years, doesn't come close.
Also: I've used Linux for 30 years. 5 reasons why I'll never switch to Windows or MacOS
You may ask yourself, "Why 19 years?" SUSE General Manager of Business Critical Linux (BCL) Rick Spencer, explained in an interview that the reason is that on 03:14:08 Greenwich Mean Time (GMT, aka Coordinated Universal Time) Tuesday, January 19, 2038, we reach the end of computing time. Well, not really, but Linux, and all the other Unix-based operating systems, including some versions of MacOS, reach what's called the Epoch.
That's when the time-keeping code in 32-bit Unix-based operating systems reaches the end of the seconds it's been counting since the beginning of time — 00:00:00 GMT on January 1, 1970, as far as Linux and Unix systems are concerned — and resets to zero. Just like the Y2K bug, that means that all unpatched 32-bit operating systems and software will have fits. The Linux kernel itself had the problem fixed in 2020's Linux 5.6 kernel, but many other programs haven't dealt with it.
Until then, though, if you're still running SLES 15 SP6, you'll be covered. I strongly suggest upgrading before then, but if you want to stick with that distro to the bitter end, you can.
Also: These 5 Linux file managers are better than what you're using now — and they're free
In addition, the new SLES boasts an updated 6.4 kernel version. It also includes new libraries, such as OpenSSL 3.1, ensuring security in compliance with strict regulations.
As for security, SLES now boasts superior confidential computing support, which encrypts your data not only when it's stored or in transit on the internet, but in memory as well. SLES provides this extra level of security on systems using Intel TDX (Trust Domain Extensions) and AMD SEV (Secure Encrypted Virtualization) processors. This includes remote attestation with SUSE Manager, ensuring end-to-end capabilities for maximum security and compliance.
SAP users will also be happy to see SLES for SAP Applications 15 SP6: This release provides SAP customers and partners with a secure and reliable Linux platform for running mission-critical SAP workloads, from the data center to the cloud. It includes access to the latest innovations from Trento, an open-source web application that helps system administrators avoid common infrastructure problems with SAP systems that can result in delayed service implementations or unplanned downtime.
If you prefer a more lightweight Linux distro for edge computing or smaller servers, SUSE also released SUSE Linux Enterprise Micro 6.0. This immutable, lightweight, and secure open-source host operating system is optimized for containerized and virtualized workloads. It simplifies standalone container deployments and provides a stable platform for Kubernetes deployments. It also includes full disk encryption support to strengthen your data security.
SUSE is also building its own platform for AI using its Linux distros called SUSE AI. This is not your usual AI play. Instead of coming up with its own Large Language Model (LLM) and chatbot, SUSE is providing the tools companies need to build their own private and secure AI programs. For example, if you want to use your own data without worrying about someone looking over your virtual shoulder to create an AI-smart troubleshooter for your products, SUSE enables you to build just that.
Also: 5 Linux commands you need to know to troubleshoot problems
On one side of the main SUSE family is SUSE's latest Linux release, SUSE Liberty Lite Linux. This distro is a replacement for CentOS 7, which, while still very popular, will reach the end of its supported life on June 30. SUSE's answer is a true drop-in replacement. You can literally just change your repositories from CentOS to Liberty Lite and keep operating.
Moreover, Liberty Linux Lite is the first Linux distro built on the Open Enterprise Linux Association (OpenELA) Linux code base. In OpenELA, CIQ, Oracle, and SUSE joined forces to create a Linux code base for RHEL clones.
Regardless of what SLES you're running, you can use SUSE Manager 5.0 to keep tabs on your server and Linux instances. Indeed, SUSE Manager supports far more than just the SLES family. It now supports over 16 different Linux distributions. These include Red Hat Enterprise Linux (RHEL), its numerous clones; Debian; Mint; and Ubuntu Linux. Indeed, you can even use it with Raspberry Pi OS, formerly Raspian, so you can manage your Raspberry Pis as well as your big iron.
Also: Why I use the Linux tree command daily — and what it can do for you
SUSE Manager, based on the Salt DevOps systems, delivers automated patch and compliance management for any Linux, anywhere and at any scale. It is containerized for increased resilience, scalability, and portability, and adds remote attestation capabilities for SLEX 15 SP6.
Get the picture? SUSE remains fully committed to the SLES. In fact, the company is already working on additional innovations for the next major release of its flagship business-critical Linux platform: SLES 16 and SLES for SAP Applications 16, coming in 2025. Tomorrow looks bright for both SUSE and Linux.
Brett Adcock, founder of Figure and Cover, has unveiled a potentially life-saving project aimed at preventing school shootings in the US. In a bold move, Adcock is personally investing a whopping $10 million into this advanced AI hardware initiative through his company, Cover.
The project leverages cutting-edge technology licensed from NASA’s Jet Propulsion Laboratory, focusing on high-frequency terahertz imaging. These advanced imaging scanners are designed to detect concealed weapons with unprecedented accuracy and safety, operating at frequencies ten times higher than current airport scanners and with a stand-off distance of up to four meters.
In the US, the number of school shootings has surged from 20 incidents in 1970 to 251 in 2021. Most victims (77%) and shooters (96%) were male, with nearly two-thirds of shooters under 17 years old. It is noted that handguns were the most common weapon, used in 84% of shootings, followed by rifles (7%) and shotguns (4%).
Adcock highlighted that the innovative scanners will be strategically placed at school entrances, capable of detecting concealed weapons in backpacks, pockets, and waistbands. The technology’s core strength lies in its hardcore AI focus, enabling autonomous object detection with minimal human intervention and low false positives.
While the primary focus is on schools, Adcock emphasised the broader potential applications fo this technology. “In the future, imaging systems like these could become ubiquitous in public venues, including airports, stadiums, concerts, churches, and more,” he explained.
Brett Adcock is a technology entrepreneur and the founder/CEO of Figure, an AI robotics company developing a general-purpose humanoid. He also founded Archer Aviation, an electric aerospace company that went public on the New York Stock Exchange in September 2021 with a valuation of $2.7 billion.
Additionally, Adcock founded Vettery, an online recruiting marketplace acquired by The Adecco Group for $110 million in an all-cash deal.
Hewlett Packard Enterprise (HPE) and NVIDIA announced NVIDIA AI Computing by HPE, a portfolio of co-developed AI solutions and joint go-to-market integrations that enable enterprises to accelerate adoption of generative AI.
Among the portfolio’s key offerings is HPE Private Cloud AI, a first-of-its-kind solution that provides the deepest integration to date of NVIDIA AI computing, networking and software with HPE’s AI storage, compute and the HPE GreenLake cloud.
The offering enables enterprises of every size to gain an energy-efficient, fast, and flexible path for sustainably developing and deploying generative AI applications.
Powered by the new OpsRamp AI copilot that helps IT operations improve workload and IT efficiency, HPE Private Cloud AI includes a self-service cloud experience with full lifecycle management and is available in four right-sized configurations to support a broad range of AI workloads and use cases.
All NVIDIA AI Computing by HPE offerings and services will be available through a joint go-to-market strategy that spans sales teams and channel partners, training and a global network of system integrators — including Deloitte, HCLTech, Infosys, TCS and Wipro — that can help enterprises across a variety of industries run complex AI workloads.
Announced during the HPE Discover keynote by HPE President and CEO Antonio Neri, who was joined by NVIDIA founder and CEO Jensen Huang, NVIDIA AI Computing by HPE marks the expansion of a decades-long partnership and reflects the substantial commitment of time and resources from each company.
“Generative AI holds immense potential for enterprise transformation, but the complexities of fragmented AI technology contain too many risks and barriers that hamper large-scale enterprise adoption and can jeopardize a company’s most valuable asset – its proprietary data.
“To unleash the immense potential of generative AI in the enterprise, HPE and NVIDIA co-developed a turnkey private cloud for AI that will enable enterprises to focus their resources on developing new AI use cases that can boost productivity and unlock new revenue streams,” said Neri.
“Never before have NVIDIA and HPE integrated our technologies so deeply – combining the entire NVIDIA AI computing stack along with HPE’s private cloud technology – to equip enterprise clients and AI professionals with the most advanced computing infrastructure and services to expand the frontier of AI,” Huang added.
