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As artificial intelligence captures the zeitgeist of society, companies such as Google, Microsoft, and NVIDIA have become major players in the race to develop AI. In 1848, during the California Gold Rush, many people focused on gold mining. Others found it equally important to provide prospectors with vital tools and equipment. These enterprising people became known as the “picks and shovels” who brought about the gold rush. They supplied pickaxes, shovels, pots and other mining equipment essential to gold prospectors. By serving the needs of miners, pick and shovel companies played a key role in supporting the gold mining rush and, in the case of Levi Strauss, built a business that continues to this day. It’s easy to draw parallels between his gold rush of 1848 and his AI technology rush of 2023.
Three companies are getting disproportionate attention. Microsoft with its investment in ChatGPT, Google with its Bard product, and NVIDIA as an arms supplier with H100 and A100 GPUs. However, these vendors are only part of the generative AI environment. Perhaps the largest market addressable is enterprise AI, where companies train AI models against their own internal private datasets. Here are five vendors that are well suited to provide the underlying infrastructure for enterprise AI.
IBM
IBM has invested in artificial intelligence for decades, demonstrating its capabilities through high-profile projects such as computer systems beating chess grandmasters and Jeopardy champions. Recently, IBM introduced watsonX at its annual Think conference. The platform aims to bring advanced AI capabilities to enterprise businesses, allowing enterprises to rapidly scale their initiatives. WatsonX consists of his three components, a base model and his WatsonX.ai design studio for generative AI. watsonX.data, an open, hybrid data store for analytics and AI workloads. and WatsonX governance focused on responsible and transparent AI. The platform provides a comprehensive technical stack that can be trained to deploy and support AI capabilities across various cloud environments. IBM’s focus on enterprise-centric AI and our collaboration with ecosystem partners demonstrates our commitment to making AI accessible and impactful for business. The company’s announcement establishes IBM as an early leader in the enterprise AI space and will lay the groundwork for the company’s future destiny.
elastic
Elasticsearch is an open source project that has become very popular among developers around the world over the last few years. The company’s revenue model is based on the developer’s commercial use of his free version of Elasticsearch, which will eventually transition into a commercial relationship. The relationship between open source adoption and commercial use is inherently embedded in Elastic’s business model, enabling expansion into various industries such as log analysis and security threat hunting.
I recently had the opportunity to speak with CEO Ashutosh Kulkarni about the company’s trajectory. The discussion focused on the challenges and opportunities of leveraging generative AI in enterprise applications, emphasizing the importance of combining proprietary data with public language models. His role of Elastic as a bridge between these two areas, as well as the company’s ability to enable companies to use specific data to enhance the context and relevance of language model output at scale It’s starting to get noticed. A key component of the company’s approach is to provide models with contextual information that will be important as enterprise AI matures, enabling Elastic as a key tool for optimizing infrastructure and improving the accuracy of AI-generated answers. Relevance Engine.
Oracle
Oracle has been a leading provider of enterprise software for decades and is recognized by many companies as the leading provider of storage of mission-critical data in database solutions. Another key component of Oracle’s portfolio is for enterprise applications that perform CRM and key back-office functions, among others. For example, the acquisition of Cerner gave Oracle access to a vast data corpus for the healthcare industry.
Oracle recently announced a partnership with Cohere to develop generative AI services for organizations around the world. The partnership aims to automate business processes, improve decision-making and enhance the customer experience. Built on Oracle Cloud Infrastructure (OCI) and powered by Oracle’s Supercluster capabilities, Oracle’s generative AI service offers high levels of security, performance, and value for enterprises deploying Enterprise AI. Cohere leverages the platform’s powerful GPU cluster technology to train and deploy generative AI models on OCI. By integrating Cohere’s models into Oracle’s cloud applications such as Fusion Cloud Applications and NetSuite, customers will be able to deploy generative AI to solve their business challenges. Oracle’s comprehensive portfolio of cloud applications, combined with Cohere’s large scale language models, provides the data security, powerful models, embedded AI services, generative intelligence, and analytics companies need to scale their enterprise AI projects. Provide AI availability.
lenovo
Many people would think of Lenovo as a provider of desktops and laptops, and that’s correct, as the company has market-leading shares in these areas. However, this is only part of the story. Lenovo is also the fourth-largest provider of enterprise storage, well-positioned to provide the underlying technology for companies adopting enterprise AI.
I recently had dinner with Kirk Skaugen, senior vice president of Lenovo’s Infrastructure Solutions Group, to discuss key investments Lenovo is making. That investment was highlighted in an announcement the company made about his AI the next day. We’ve detailed those announcements here. Lenovo is demonstrating its commitment to simplifying AI deployments and delivering end-to-end infrastructure solutions, ultimately delivering tools that enable organizations of all sizes to harness their transformative power, leading to enterprise innovation. Suffice it to say that it will be a player in providing the underlying infrastructure for AI. Leveraging AI across industries.
Hewlett Packard Enterprise
Hewlett Packard Enterprise (HPE) recently entered the AI market with a new cloud service called HPE GreenLake for Large Language Models (LLM). The service will give enterprises access to NVIDIA H100 GPUs and data science tools handpicked by HPE’s Cray Super Computing division to sustainably train, tune and deploy AI at scale. . why is this important? Access to NVIDIA kits is now a major constraint on companies’ AI ambitions, and HPE has nearly eliminated this problem with the launch of this new service.
Based on a recent 1-2-1 briefing from HPE, the company will release more industry-specific AI applications in the future, focusing on areas such as climate modeling, healthcare, finance, manufacturing and transportation intend to do something. The service differentiates itself by addressing performance, data management, security, and reliability concerns, while providing a trusted environment through single-tenant nodes, according to the company. HPE’s partnership with his AI company in Europe, Aleph Alpha, will help streamline model development and accommodate European culture and, more importantly, regulation. Sustainability is also a key consideration, with initial deployments in Quebec, Canada, where comprehensive efforts have been made to address GPU power consumption and the resulting environmental impact from the start. increase.
The initial details are impressive, but to get a more complete picture, the service needs to be seen at scale in real-world deployment scenarios. Check out this space.
looking to the future
With thousands of startups vying for VC capital to grow their businesses in the AI space, and many of them eyeing enterprise AI use cases, the field is certainly dynamic and evolving. . However, busy executives must fight the urge to chase the latest and brightest solutions. They should look to enduring companies like the ones highlighted above and work with them to deliver a robust enterprise AI platform that will underpin their AI ambitions for years to come.
By providing advanced AI capabilities, bridging proprietary and public models, providing secure storage solutions, and providing generative AI services, these “pick and shovel” providers are critical in shaping the future of enterprise AI. in a position to play a role. These companies, and the efforts they are making to work together to address the challenges, are driving innovation and the proliferation of AI technologies.
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