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Nvidia has been talking about AI factories for some time, and now it’s coming out with some reference designs to help build them. The chipmaker has released a series of what it calls EnterpriseReference Architectures (Enterprise RA), which are blueprints to simplify the building of AI-oriented data centers.
IBM has broadened its support of Nvidia technology and added new features that are aimed at helping enterprises increase their AI production and storage capabilities. The IBM AI Integration service already supports a number of third-party systems, including Oracle, Salesforce, SAP and ServiceNow environments.
But a lot of the proprietary value that enterprises hold is locked up inside relational databases, spreadsheets, and other structured file types. For example, if an LLM is asked to provide information about a companys product, manuals for that product and other reference materials would be extremely helpful.
As IT professionals and business decision-makers, weve routinely used the term digital transformation for well over a decade now to describe a portfolio of enterprise initiatives that somehow magically enable strategic business capabilities. Ultimately, the intent, however, is generally at odds with measurably useful outcomes.
Today, I am happy to announce the publication of the Forrester Reference IT Capability Map. This is a comprehensive, mutually exclusive and comprehensive statement of the major capabilities used to define and deliver IT and digital systems, individually and at a portfolio level.
The reference architecture is actually a hybrid liquid- and air-cooling infrastructure that simplifies and accelerates deployment of AI workloads in new and existing data centers and enables standardization across sites. With their joint design, Vertiv and Nvidia are offering liquid cooling support for up to 132 kW per rack.
Hewlett Packard Enterprise (HPE) and Supermicro have separately announced new liquid cooling products to keep up with the heat generated by large-scale AI deployments. In the case of HPE, it showed off a design that offers direct liquid cooling without an expensive component: the fans.
Enterprises are wrestling with a gamut of tools and technologies that are always changing, he says. The system integrator has the Topaz AI platform, which includes a set of services and solutions to help enterprises build and deploy AI applications. The updated product also has enhanced security features, including LLM guardrails.
The Ethernet Alliances roadmap references the consortiums 2024 Technology Exploration Forum (TEF), which highlighted the critical need for collaboration across the Ethernet ecosystem: Industry experts emphasized the importance of uniting different sectors to tackle the engineering challenges posed by the rapid advancement of AI.
The term was coined by Gartner in 2023, but the concept has existed in different iterations for some time, with other vendors and analysts referring to it as autonomous networking, intent-based networking, and self-driven or self-healing networking.
integrates what Red Hat refers to as VM-friendly networking. With OpenShift 4.18, Red Hat is integrating a series of enhanced networking capabilities, virtualization features, and improved security mechanisms for container and VM environments. In particular, OpenShift 4.18
By 2028, 40% of large enterprises will deploy AI to manipulate and measure employee mood and behaviors, all in the name of profit. “AI By 2028, 25% of enterprise breaches will be traced back to AI agent abuse, from both external and malicious internal actors.
Intel has introduced a reference design it says can enable accelerator cards for security workloads including secure access service edge (SASE), IPsec, and SSL/TLS. Get regularly scheduled insights by signing up for Network World newsletters. ]. Get regularly scheduled insights by signing up for Network World newsletters. ].
Copilot Studio allows enterprises to build autonomous agents, as well as other agents that connect CRM systems, HR systems, and other enterprise platforms to Copilot. Then in November, the company revealed its Azure AI Agent Service, a fully-managed service that lets enterprises build, deploy and scale agents quickly.
It’s a position many CIOs find themselves in, as Guan noted that, according to an Accenture survey, fewer than 10% of enterprises have gen AI models in production. “What’s Next for GenAI in Business” panel at last week’s Big.AI@MIT It’s time for them to actually relook at their existing enterprise architecture for data and AI,” Guan said.
The enhancements aim to provide developers and enterprises with a business-ready foundation for creating AI agents that can work independently or as part of connected teams. Llama is the most widely used open model across every enterprise, but it didnt have reasoning.
When I joined VMware, we only had a hypervisor – referring to a single software [instance] that can be used to run multiple virtual machines on a physical one – we didn’t have storage or networking.” VMware’s origins To understand Baguley’s career at the company, you have to look back 13 years and six months.
For network engineers and security leaders tasked with securing modern enterprise environments, the challenge of preventing lateral threat movement is critical. The resulting solution sprawl has resulted in a lack of consistent east-west visibility, making centralized policy management impossible inside enterprise networks.
The news came at SAP TechEd, its annual conference for developers and enterprise architects, this year held in Bangalore, the unofficial capital of India’s software development industry. There’s a common theme to many of SAP’s announcements: enabling enterprise access to business-friendly generative AI technologies. “We
When the endpoint detection and response (EDR, which was also referred to as endpoint threat detection and response, or ETDR, at the time) market was getting started, there was a lot of pushback, ranging from privacy concerns to what the acceptance of a second security agent on endpoints would be (apparently, it was never going […].
Between building gen AI features into almost every enterprise tool it offers, adding the most popular gen AI developer tool to GitHub — GitHub Copilot is already bigger than GitHub when Microsoft bought it — and running the cloud powering OpenAI, Microsoft has taken a commanding lead in enterprise gen AI.
Today, that vision became a reality with the general availability of Red Hat Enterprise Linux AI. RHEL AI is Red Hat’s solution to the problems enterprises have building and deploying AI across hybrid clouds and the high costs of training and inference. That includes immediate support for Nvidia hardware.
Cisco and Nvidia have expanded their partnership to create their most advanced AI architecture package to date, designed to promote secure enterprise AI networking. Nvidia AI Enterprise software platform, which featurespretrained models and development tools for production-ready AI. Nvidia AI Enterprise software platform.
The enterprise edge has become a growing area of innovation as organizations increasingly understand that not every workload — particularly new edge workloads — can move to the cloud. We refer to them as “deploy the edge” and “run the edge.” This presents a critical sustainability challenge.
The Open Group Architecture Framework (TOGAF) is an enterprise architecture methodology that offers a high-level framework for enterprise software development. The TOGAF certification is especially useful for enterprise architects , because it’s a common methodology and framework used in the field. TOGAF definition.
Meanwhile, AI Insight Broker refers to the packet brokers with these AI capabilities built-in. Finance will have a different requirement than service providers, than the government, than enterprises. The AI Stack serves as an umbrella framework for AI-related features implemented in Keysights packet brokers.
A move that is likely to unlock similar investments from competitors — Google in particular — and open the way for new or improved software tools for enterprises large and small. Up to that point, OpenAI had only allowed enterprises and academics access to the software through a limited API.
Deepak Jain, 49, of Potomac, was the CEO of an information technology services company (referred to in the indictment as Company A) that provided data center services to customers, including the SEC,” the US DOJ said in a statement. From 2012 through 2018, the SEC paid Company A approximately $10.7
What is enterprise service management? Enterprise service management (ESM) is the practice of applying IT service management (ITSM) principles and capabilities to improve service delivery in non-IT parts of an organizations, including human resources, legal, marketing, facilities, and sales. Benefits of enterprise service management.
“You cannot just rely on the firewall on the outside, you have to assume that any application or any user inside your data center is a bad actor,” said Manuvir Das, head of enterprise computing at Nvidia. Zero Trust basically just refers to the fact that you can't trust any application or user because there are bad actors.”
Now, generative AI use has infiltrated the enterprise with tools and platforms like OpenAI’s ChatGPT / DALL-E, Anthropic’s Claude.ai, Stable Diffusion, and others in ways both expected and unexpected. In my next article, I’ll share some processes to manage and remediate the use of generative AI in enterprise organizations. Stay tuned!
For reference, McKinsey research estimates that there was 25 gigawatts worth of demand in 2024. In addition to working with data center providers to ensure long-term access to capacity, enterprises are also casting a wider geographical net, looking towards renewables, and considering fuel cells to power on-prem data centers.
Forrester just published new research outlining the future of small and midsize business banking (also called SME banking to refer to SMEs, or small- and medium-sized enterprises). If you’re an executive at a traditional bank, it contains some grim and gloomy predictions.
Goodwin explains that the traditional approach to inference is that the AI chip needs to refer back to the training model database, which is stored in DRAM, and could account for terabytes of memory that needs to move from storage to compute. How could Fractile benefit enterprises?
SUSE is preparing an “enterprise-grade generative AI Platform” that will run any vendor’s large language models (LLMs) on premises or in the cloud, it said Tuesday. For many enterprises, the on-prem vs cloud debate is more about control than anything else. They are hedging their bets.” The jury is out on the cost tradeoffs,” Iams said.
Being on the forefront of enterprise storage in the Fortune 500 market, Infinidat has broad visibility across the market trends that are driving changes CIOs cannot ignore. Enterprise storage cyber resilience continues to need to be part of your corporate cybersecurity strategy. This is a multi-faceted trend to keep front and center.
On the contrary, vendors like IBM, Oracle and SAP remain very committed to continuing to support enterprise offerings that they first introduced decades ago. The meaning of legacy system modernization can be a bit challenging to pin down because IT leaders often use the term to refer to two fundamentally different processes.
TIAA has launched a generative AI implementation, internally referred to as “Research Buddy,” that pulls together relevant facts and insights from publicly available documents for Nuveen, TIAA’s asset management arm, on an as-needed basis. Vendors are providing built-in RAG solutions so enterprises won’t have to build them themselves.
If you’re an enterprise, your network and IT spending are likely under pressure…except for security. Security has gotten too complicated , according to every enterprise who’s offered me an opinion. Said one, “I’m not sure if [my vendor] is Gandalf or is forging the One Ring,” a reference to Tolkien’s fantasy classic.
Afterward, we spent some time drilling down into what they refer to as the “seven minimums of AdaptiveEXECUTION,” a set of practices that ensure an organization can not only keep up with the pace of change but lead it. What follows is that conversation, edited for length and clarity.
Google Cloud has updated its managed compute service Cloud Run with a new feature that will allow enterprises to run their real-time AI inferencing applications serving large language models (LLMs) on Nvidia L4 GPUs. To being with, enterprises may worry about cold start — a common phenomenon with serverless services.
Samsung, in particular, is in a bind as it has struggled to gain a foothold in AI and now has to give up one of its largest markets in China,” said Park, referring to the significant share of Samsung’s HBM chip sales generated in the Chinese market.
Being on the leading edge of network and information systems technology comes with its challenges, and enterprises say one challenge, in particular, is growing every year. Of 298 enterprise professionals who commented on hiring and staff skill sets, 221 were hiring people to work with technologies the company already had in use.
Download our editors PDF SASE and SSE enterprise buyers guide today! Enterprises deal with fewer vendors, the amount of hardware required in branch offices and other remote locations declines, and the number agents on end-user devices also decreases. billion by 2025. What are the benefits of SASE? What are the SASE challenges?
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