Chipmakers Now Ship Protein-Folding AI as Plug-and-Play Microservices

News Provided by American News Group on behalf of MindWalk Holdings Corp.

AUSTIN, Texas, Sept. 22, 2026 (GLOBE NEWSWIRE) -- American News Group News Commentary - For most of the last decade, predicting the three-dimensional shape of a protein complex was the kind of capability only a well-funded research organization could stand up. That is changing quickly. Open-source structure prediction models are now freely licensed for commercial use, and the largest chipmakers are packaging them as ready-to-deploy inference microservices that can be launched from a cloud marketplace. The Business Research Company projects the AI protein structure prediction market will grow from about $2.33 billion in 2026 to roughly $6.62 billion by 2030, a compound annual growth rate of approximately 29.8%. As the model itself becomes easier to obtain, the question for drug discovery shifts to what a company brings to it. Companies mentioned in today's commentary include: MindWalk Holdings Corp. (NASDAQ: HYFT), Advanced Micro Devices, Inc. (NASDAQ: AMD), NVIDIA Corporation (NASDAQ: NVDA), CoreWeave, Inc. (NASDAQ: CRWV), and Nebius Group N.V. (NASDAQ: NBIS).

Key Takeaways

• Structure prediction is standardizing. OpenFold3, an open-source biomolecular structure prediction model, is available under the Apache 2.0 license for academic and commercial use, and is offered as a packaged microservice by both NVIDIA and AMD.
• MindWalk ran real programs through it. MindWalk reported results from its independent validation of AMD Inference Microservices for OpenFold3 on Vultr, including a production prediction environment deployed in minutes and antibody-antigen inference roughly 5x faster than in its prior environment.
• The model is not the moat. OpenFold3 is not a MindWalk model. The Company frames the validation as evidence of a model-agnostic platform whose value sits in its own biological representation rather than in any single model.
• Compute is scaling on every front. AMD, NVIDIA, CoreWeave and Nebius have each reported rapid growth in AI infrastructure demand, widening the options for routing high-compute biology workloads.

The Model Is No Longer the Scarce Part

OpenFold3 was developed by the AlQuraishi Lab at Columbia University and the OpenFold Consortium, a nonprofit research group, as an open reproduction of the architecture behind AlphaFold3. It predicts the structures of proteins, RNA, DNA and small molecules, and their complexes. Unlike AlphaFold3, which carries restrictions on commercial use, OpenFold3 is released under the permissive Apache 2.0 license. In March 2026, the Consortium went further and released training datasets, model weights, and training and inference code, so that the community can inspect, retrain and extend the model rather than simply run it.

The silicon vendors have followed. NVIDIA offers OpenFold3 as a downloadable microservice through its BioNeMo platform, and in June 2026 Advanced Micro Devices, Inc. (NASDAQ: AMD) said Vultr was bringing its enterprise AI software, including a catalog of AMD Inference Microservices (AIMs) built by AMD Silo AI and optimized for AMD Instinct GPUs, to the Vultr Marketplace. Per AMD, AIMs are containerized inference microservices with standardized model serving. The practical result is that a biology team can now reach a production-grade structure prediction endpoint through a marketplace transaction instead of a multi-year infrastructure project.

What MindWalk Put Through the Pipeline

MindWalk Holdings Corp. (NASDAQ: HYFT) a Bio-Native AI company, reported results from its independent validation of AMD Inference Microservices for OpenFold3 running on Vultr Kubernetes Engine and Vultr Cloud GPU powered by AMD Instinct™ MI325X GPUs. According to the Company, a production-grade prediction environment deployed in minutes, and antibody-antigen inference time fell by approximately 5x against MindWalk's prior environment. The Company notes that the results reflect the specific configurations evaluated and are not representative of all workloads.

MindWalk says it supplied production-oriented drug discovery workloads rather than a curated benchmark set: single- and multi-chain proteins, protein-RNA and protein-DNA interactions, protein-ligand structures using CCD and SMILES inputs, and antibody-antigen complexes. It exercised the complete path, including CPU-intensive preprocessing and multiple sequence alignment alongside GPU-accelerated inference.

“Antibody-antigen prediction is the workload we care most about, and it has always been the one where infrastructure got in the way,” said Dr. Jennifer Bath, PhD, Chief Executive Officer and President of MindWalk. “Standing up a production environment in minutes, and seeing complexes of that size come back in seconds, changes how many hypotheses a team can afford to test in a week. That is the practical effect, and it is why we put real programs through this rather than a benchmark set chosen to look good.”

The evaluation also surfaced practical considerations around multi-GPU execution, inference controls and deployment workflows, which MindWalk says it returned to inform subsequent platform work. In the Company's words, that feedback loop, rather than the timings, is what an evaluation of this kind is for.

Why the Value Moves to the Layer Beneath the Model

MindWalk's argument is that the validation demonstrates rather than asserts a model-agnostic posture. The Company deployed, ran and measured a third-party open-source model on third-party infrastructure, inside its own discovery workflows and under its own governance and human review, and says customers choosing to run their own models face the same path. It describes Vultr, AWS and AMD as the compute fabric beneath its platform, with high-compute work directed to the provider whose price-performance fits the workload, and notes that inference efficiency at this layer bears on the cost of delivering AI workflows to customers.

If prediction itself is standardizing, the differentiator becomes what sits underneath it. At the core of MindWalk's platform is HYFT® Technology, a proprietary, function-aware representation of biology that, refined over 20 years of curation, forms a biological representation of 660 million patterns and 25 billion relationships. That representation underpins ReefIQ™, the biological context layer for life sciences, and LensAI™, the reasoning and application layer for target discovery, candidate diligence, portfolio decision support and agentic AI workflows. By the Company's design, value compounds in this representation layer, not in any individual AI model that runs on top of it.

The Company also points to a customer-side benefit: a standardized, Kubernetes-native path from open model to production workflow shortens the distance between a research question and an answer inside a regulated environment, which MindWalk says is the operational objection pharmaceutical CIOs raise most often. AMD Inference Microservices for OpenFold3 are available through the Vultr Kubernetes Engine Marketplace as part of the AMD Enterprise AI Software stack.

There are several risks associated with the Company's plans. The results described come from specific evaluated configurations and may not be representative of other workloads, inputs or environments, and the multi-GPU, inference-control and deployment considerations identified during the evaluation may take time to resolve. MindWalk relies on third-party cloud, GPU, microservice and open-source model providers whose availability and pricing may change. The Company has identified the risk that technical validation does not convert into contracted, recurring arrangements, alongside risks tied to compliance capabilities for regulated workloads, competition, intellectual property and capital markets conditions. Investors should review MindWalk's Annual Report on Form 20-F and other filings on SEDAR+ and EDGAR.

The Compute Layer Is Scaling Fast

The other side of standardization is capacity. The companies building and renting AI compute have reported some of the fastest growth in the market, which widens the menu of places a biology workload can run.

Advanced Micro Devices, Inc. (NASDAQ: AMD)

Advanced Micro Devices, Inc. (NASDAQ: AMD) supplies the Instinct accelerators and the software stack referenced in the validation work described above. Its AI Inference Microservices catalog is built by AMD Silo AI and optimized for AMD Instinct GPUs, and is available through the Vultr Marketplace as part of the AMD Enterprise AI Software stack. The microservices are containerized, which is the property that lets an organization deploy a packaged model without assembling the underlying inference environment itself.

AMD reported second-quarter 2026 revenue of $11.5 billion, up 50% year over year and a Company record, with gross margin of 54%, operating income of $2.0 billion, net income of $2.3 billion and diluted earnings per share of $1.38. On a non-GAAP basis, gross margin was 56%, operating income was $3.1 billion, net income was $2.8 billion and diluted earnings per share was $1.66. Data Center segment revenue was $6.7 billion, up 107% year over year, driven by demand for AMD EPYC processors and AMD Instinct GPUs, and represented 58% of company revenue in the quarter. For the third quarter of 2026 AMD guided to revenue of approximately $13 billion, plus or minus $300 million, representing year-over-year growth of approximately 41% at the midpoint.

“We delivered an excellent quarter, with record revenue and profitability as Data Center revenue more than doubled year-over-year,” said Dr. Lisa Su, AMD chair and CEO. “We enter the second half with strong momentum as EPYC demand accelerates, Instinct deployments scale and Helios begins to ramp.”

NVIDIA Corporation (NASDAQ: NVDA)

NVIDIA Corporation (NASDAQ: NVDA) reported second-quarter fiscal 2027 revenue of $96.2 billion, up 106% from a year ago, with Data Center revenue of $89.0 billion, up 117%. The company returned approximately $26.0 billion to shareholders during the quarter through share repurchases and dividends. Its CEO pointed to a thriving open-model ecosystem among the forces driving demand, the same dynamic that has pushed models such as OpenFold3 into packaged, deployable form through its BioNeMo platform.

“AI has reached its inflection point. It's doing useful work. Its tokens are productive and profitable. Now, compute is revenue,” said Jensen Huang, founder and CEO of NVIDIA.

CoreWeave, Inc. (Nasdaq: CRWV)

CoreWeave, Inc. (Nasdaq: CRWV), which describes itself as The Essential Cloud for AI™, reported a revenue backlog of approximately $104 billion as of June 30, 2026, and said it had added more than $25 billion of net new customer commitments in early Q3 that are not included in that figure. The company expanded active power by nearly 500 MW to reach 1.5 GW and grew total contracted power to approximately 3.7 GW. Among the enterprises and AI pioneers it named as customers is Isomorphic Labs, the AI drug discovery company, alongside Bentley Systems, Caterpillar, Grammarly and Sunday Robotics.

“CoreWeave reached an important inflection point this quarter as our scale began to translate into expanding operating leverage,” said Michael Intrator, co-founder, chairman and chief executive officer of CoreWeave.

Nebius Group N.V. (NASDAQ: NBIS)

Nebius Group N.V. (NASDAQ: NBIS), the Amsterdam-headquartered AI cloud company, reported second-quarter 2026 revenue of $582.3 million, up 454% from $105.1 million a year earlier, with adjusted EBITDA of $236.2 million compared with a loss of $21.0 million in the prior-year quarter. Non-current deferred revenue rose to approximately $5.0 billion at June 30, 2026 from $1.3 billion at the end of 2025, according to the company's balance sheet.

Nebius runs a dedicated Scientific AI and Healthcare practice among its cloud solutions, and in July 2026 it held an expanded AI Discovery Awards program recognizing healthcare and life sciences innovators, an indication of how actively the AI clouds are now courting biology workloads.

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Article Sources:
[1] MindWalk Holdings Corp., press release on its validation of AMD Inference Microservices for OpenFold3 on Vultr Kubernetes Engine (validation results, CEO commentary, platform description).
[2] OpenFold Consortium releases and the OpenFold3 model documentation (licensing, capabilities, March 2026 full-stack release).
[3] AMD, “Vultr Enables Enterprise AI with Software Components from AMD,” June 15, 2026; NVIDIA BioNeMo OpenFold3 model card.
[4] The Business Research Company, Artificial Intelligence (AI) Protein Structure Prediction Market Report 2026.
[5] Company releases of NVIDIA (Aug. 26, 2026), CoreWeave (Aug. 11, 2026) and Nebius (Aug. 12, 2026).

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Cautionary Note Regarding Technology Validation and Third-Party Platforms. The validation results described in this publication are MindWalk Holdings Corp.'s own reported results for the specific configurations it evaluated, have not been independently verified by the publisher, and may not be representative of other workloads, inputs or environments. OpenFold3 is a third-party open-source model developed by the OpenFold Consortium and the AlQuraishi Lab at Columbia University and is not a MindWalk product. Descriptions of AMD, AMD Instinct™ GPUs, AMD Inference Microservices, Vultr, NVIDIA BioNeMo and related products are paraphrased from those companies' public disclosures and are not MindWalk product claims. References to AMD, Vultr, AWS, NVIDIA or the OpenFold Consortium do not imply endorsement, sponsorship or partnership by any of them, or any commercial relationship with MindWalk beyond what MindWalk has itself disclosed. Any MindWalk product candidates or therapeutic programs are investigational and have not been approved by any regulatory authority.

Cautionary Note Regarding Referenced Companies. References to Advanced Micro Devices, Inc., NVIDIA Corporation, CoreWeave, Inc. and Nebius Group N.V. are provided solely as market and sector context regarding AI compute infrastructure. Those companies are not peers, competitors, or financial comparables of MindWalk Holdings Corp., differ substantially from it in size, stage, capitalization and business model, and are not involved in the preparation or distribution of this publication. Their results and share performance describe those companies only and are not indicative of MindWalk's prospects. No partnership, affiliation, or endorsement is implied. Market-size figures cited are third-party projections, are not MindWalk's addressable revenue, and may not be realized.

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