<div>
  <ul>
    <li>
      <p>
        Nvidia announced that it has entered a definitive agreement to acquire Run:ai, a Kubernetes-based workload management and orchestration software provider, to help customers use their AI computing resources more efficiently. The terms of the deal were not disclosed, but reports suggest that the price tag was USD 700 million.
      </p>
    </li>
    <li>
      <p>
        Based in Israel, Run:ai offers enterprise customers a comprehensive solution to manage and optimize their compute infrastructure across on-premises, cloud, or hybrid environments. It leverages an open platform built on Kubernetes, the leading orchestration layer for modern AI and cloud infrastructure. This platform integrates with various Kubernetes variants and third-party AI tools and frameworks.
      </p>
    </li>
    <li>
      <p>
        It serves some of the world&rsquo;s largest enterprises spanning multiple industries by enabling them to efficiently manage data-center-scale GPU clusters through its platform.
      </p>
    </li>
    <li>
      <p>
        After the acquisition, NVIDIA intends to maintain Run:ai's existing products and will incorporate them into NVIDIA's DGX Cloud AI platform. This integration aims to enhance AI deployments, particularly for GenAI implementations spread across numerous data center locations, providing clients with more efficient use of their AI computing sources.
      </p>
    </li>
  </ul>
  <p>
  </p>
</div>


<div>
  <p>
    <a href="https://blogs.nvidia.com/blog/runai/">
      Company blog
    </a>
  </p>
  <p>
    <a href="https://techcrunch.com/2024/04/24/nvidia-acquires-ai-workload-management-startup-runai/">
      TechCrunch
    </a>
  </p>
  <p>
  </p>
</div>


Machine Learning Infrastructure

INCUMBENTS_PRESENT

<div>
 <p>Nvidia has confirmed its plans to acquire Run:ai, a provider of Kubernetes-based workload management and orchestration software. Though the exact terms of the agreement were not revealed, the deal is reportedly valued at $700 million. Founded in Israel, Run:ai delivers a broad solution to enterprise customers to manage and optimize their compute infrastructure in on-premises, cloud, or hybrid set-ups by using an open platform built on Kubernetes.</p>
 <p>The platform integrates with different Kubernetes variants and numerous third-party AI tools and frameworks. Run:ai caters to some of the largest global enterprises from various industries by helping them efficiently manage their data center-scale GPU clusters through its platform.</p>
 <p>Upon completion of the acquisition, Nvidia plans to continue Run:ai's existing product line and integrate them into their DGX Cloud AI platform. This step is aimed at improving AI deployments, especially for GenAI implementations distributed over multiple data center locations, thereby enabling customers to utilize their AI computing resources more efficiently.</p>
 
</div>

NVIDIA acquires AI infrastructure management company Run:ai

PROMINENT_CATEGORY

<div>
 
 <p>Meta has announced the next version of its AI infrastructure, the Meta Training and Inference Accelerator (MTIA). This custom-made AI chip is designed to power both current and future Meta products.</p>
 <p>The new MTIA features enhanced compute power and memory bandwidth capabilities. It also supports the efficient architecture needed for GenAI applications, recommendation systems, and advanced AI research. The company is also developing several programs to expand MTIA's scope, specifically concerning support for GenAI workloads.</p>
 <p>The latest MTIA offers improved power and efficiency, boasting double the compute and memory bandwidth of its predecessor. These upgrades help to enhance Meta's platform content personalization abilities.</p>
 <p>In terms of hardware, the MTIA has also seen significant improvements. It features a rack-based design that can accommodate up to 72 accelerators, an elevated clocking speed, and an upgraded fabric between the accelerators and the host. The newest version also leverages PyTorch 2.0, integrating its performance benefits and related software features.</p>
 
</div>

Meta unveils next generation of Meta Training and Inference Accelerator (MTIA)

<div>
 
 <p>A data labeling and annotation platform, Sapien, has managed to gather a total of USD 5 million in a seed funding round. Notable participants of the funding round included Primitive Ventures, Artichoke Capital, and Yield Guild Games.</p>
 <p>The funds raised will primarily be used for the acceleration of product development.</p>
 <p>Sapien's main offering is a scalable annotation service for AI model training through its data labeling platform. The focus of the platform is the creation of a network for AI training data, which is generated by humans and provided to developers via an AI data marketplace. Sapien employs a novel approach to this system, involving gamification and rewards based on blockchain, to motivate its community of human labelers to come up with accurate annotations.</p>
 
</div>

Sapien raises USD 5 million in seed funding for product development

ANALYST_QUICK_TAKE

<div>

 <p>Intel introduced its most recent AI chip, Gaudi 3, which is tailored to improve the training and implementation of complex AI models such as those used by OpenAI's ChatGPT. The chip should be commercially accessible to clients in the third quarter, yet details regarding its price aren't disclosed yet.</p>
 <p>Gaudi 3 AI from Intel will power AI systems with a large number of accelerators, potentially in the tens of thousands. Intel asserts that its chip performs better than Nvidia's H100 GPUs.</p>
 <p>These new chips are Intel's attempt to meet specific enterprise-level Machine Learning (ML) and General AI (GenAI) requirements, as well as to tackle the scaling issues that enterprises regularly confront.</p>
 
</div> <p><b>Analyst QuickTake:<br>
</b> With the Gaudi 3 chip, Intel aims to disrupt and capture a significant portion of the rapidly expanding AI chip market, which is currently dominated by Nvidia, holding approximately 80% of the market share. Moreover, late last month, Intel and the US Department of Commerce <a href="https:<br>
//sp-edge.com/updates/27828"> signed a non-binding preliminary memorandum of terms </a> (PMT) for up to USD 8.5 billion in direct funding to Intel for commercial semiconductor projects under the CHIPS and Science Act.</p>

Intel launches new AI chip Gaudi 3 to be commercially available from Q3

<div>
 
 <p>Canadian Prime Minister, Justin Trudeau, has announced the allocation of CAD 2.4 billion (~USD 1.8 billion) for enhancing the country's AI sector in the forthcoming budget. Of this, nearly CAD 2 billion (~USD 1.5 billion) will be dedicated for the development and expansion of computing capabilities and technological infrastructure for AI research. The budget presentation is scheduled for April 16, 2024.</p>

</div>

Canadian Government set to allocate CAD 2.4 billion in upcoming budget to invest in AI

<div>
 
 <p>Hugging Face, a machine learning and natural language processing platform, has formed a partnership with Wiz Research, a tech research firm. The collaboration aims to detect and handle possible security threats in Hugging Face's AI cloud services platform.</p>
 <p>With this alliance, Wiz Research is committed to enhancing Hugging Face's security measures, minimizing the potential risks associated with the shared infrastructure used for storing sensitive data.</p>
 
</div>

Hugging Face and Wiz Research partner to enhance security practices

<div>
 
 <p>SiMa.ai, a company that manufactures embedded Machine Learning System-on-Chip (SoC) platforms, has successfully raised an additional USD 70 million in a Series B extension round. This funding round was led by Maverick Capital and saw participation from several other companies such as Point72, Jericho, and Amplify Partners. With this latest funding round, SiMa.ai's total funds raised so far have reached USD 270 million.</p>
 <p>The company has plans to use this new funding to expand its operations. This includes recruiting customer service teams globally, expanding its research and development capabilities, and launching its second-generation machine learning SoC in the first quarter of 2025.</p>
 
</div> <p><b>Analyst QuickTake:<br>
</b> SiMa.ai's ML SoC platform offers developers performance and versatility across diverse computer vision tasks. The upcoming second-generation GenAI SoC will enhance performance with architectural improvements while maintaining adaptability to various frameworks, networks, models, and sensors. It will also introduce compatibility with additional modalities like audio, speech, text, and image.</p>

SiMa.ai raises USD 70 million in Series B extension for recruitment and product development

<div>
 <p>Hailo, a company that manufactures Edge AI microprocessors, has successfully raised USD 120 million in an extended Series C funding round. Investors include Alfred Akirov, Delek Motors, and VC platform OurCrowd.</p>
 <p>Alongside the funding announcement, Hailo also launched the high-performance Hailo-10 GenAI accelerator chip. The chip is designed to run AI models at the edge with lower latency, eliminating the dependence on cloud-based servers.&nbsp;</p>
</div>

Hailo raises USD 120 million; launches first chip for GenAI

<div>
 
 <p>FLock.io, a UK-based decentralized AI training platform, recently raised USD 6 million in a seed funding round. This round was co-led by Lightspeed Faction and Tagus Capital.</p>
 <p>The funds will be used to further develop FLock.io's technology and the overarching platform.</p>
 <p>The company, founded in 2022 by a group of Oxford Alumni with over a decade of experience in the AI and crypto industries, offers an innovative AI co-creation tool. Their platform, launched on March 20, employs federated learning and blockchain technologies to form an end-to-end AI creation stack.</p>
 
</div>

FLock.io raises USD 6 million in seed funding to enhance federated learning-powered training platform

<div>
 
 <p>The US Department of Commerce has agreed on a non-binding preliminary memorandum of terms (PMT) with Intel, potentially providing up to USD 8.5 billion in direct funding for commercial semiconductor projects. This falls under the CHIPS and Science Act and works towards the US government's aim to strengthen the country's semiconductor manufacturing and related supply chain sectors.</p>
 <p>This funding is set to enhance Intel’s R&amp;D and manufacturing of semiconductors at their locations in Arizona, New Mexico, Ohio, and Oregon. Furthermore, the PMT allows Intel the opportunity to access up to USD 11 billion in federal loans.</p>
 <p>Intel plans to apply for the US Treasury Department’s Investment Tax Credit (ITC), projected to be around 25% of eligible investments exceeding USD 100 billion over a period of five years.</p>
 
</div>

All Updates