Mujin raises $224 million in Series D round, linked to SK Square's bet on AI-powered physical robots
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Mujin raises $224 million in Series D round, linked to SK Square's bet on AI-powered physical robots

Amid the artificial intelligence revolution, there is a shift in technological focus towards practical applications, specifically the creation of physical robots with AI. Mujin successfully raised $224 million in a Series D funding round for the development of such robots.

One of the investors in this round is the South Korean company SK Square, which is making significant bets on the future of physical AI. Mujin, Inc., a Japanese robotics company founded in 2011, utilizes its flagship product, Mujin OS—a general-purpose platform for robot control.

Many different machines are used in most production workshops and warehouses. Typically, manipulators, conveyors, and automated guided vehicles operate in isolation. Mujin OS acts as a single central intelligence that not only powers but also connects all robots in the warehouse, making each robot smarter and allowing one system to manage the entire facility. This represents the growing trend of physical AI, as Mujin creates artificial intelligence to power physical robots.

SK Square participated in the round through its foreign investment company, TGC Square, although the amount of its investment was not disclosed. According to Korea Economic Daily, the total volume of the round exceeded 300 billion won, which is approximately $224 million.

SK Square is actively investing in AI-powered physical robots as it transforms into a semiconductor investment holding company. Since chips require factories, and factories require robots, there is a need for clear instructions for robots. SK Square has obvious areas of application within SK Group, including semiconductor packaging, logistics, and factory construction sites, as well as a broader vision for autonomous manufacturing.

SK Square expects one operating system to be able to control all logistics equipment in a chip manufacturing plant. This forecast is not unfounded, given that SK Square, being the eighth American or Japanese company in the field of AI and chips, received support from TGC Square. The previously selected company d-Matrix is now valued at over $2 billion, more than seven times its valuation at the time of SK Square's investment in 2023.

The attraction of over $224 million, which increases Mujin's total funds raised to over $500 million, demonstrates the direction of future investments. If previously most of the funds going into AI were directed towards chips and advanced models, the share of funds going towards machines with real AI applications is now increasing. This shift underscores SK Square's strategy. This new wave of value does not necessarily have to reside in the chip; it can be realized on the robotic factory where that chip is produced. This is critically important for investors, operators, and participants in any supply chain, as physical AI has the potential to revolutionize storage, sorting, and goods production, and companies like Mujin are developing the corresponding software.

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Albert raises $55 million to advance chemical AI in R&D
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Albert raises $55 million to advance chemical AI in R&D

Albert has successfully raised $55 million in a Series B funding round, with the funds designated for advancing artificial intelligence in scientific research. The leadership of this round was secured by TCV, and new investors joined, including Delta-v Capital, Socium Ventures, High Sage Ventures, Coral Capital, and Legion VC.

Truffle Capital led the financing, with participation from existing investors such as Coatue, J.P. Morgan Growth Equity Partners, Index Ventures, and Applied Ventures. The company plans to use the raised capital to further refine its chemistry-based platform.

Located in Oakland, California, Albert develops an operating system for materials science and chemistry. This platform integrates specialized AI with corporate security, management, and integration features, such as no data storage, granular access control, and audit trails of reasoning.

Albert provides services to organizations with complex research challenges facing evolving regulations and disrupted supply chains. Among the company's clients are BASF, Henkel, Clorox, Kenvue, and Akzo Nobel. Albert's goal is to help these companies' scientists faster transform experimental data into innovative products.

Albert's model, named Valence, is chemically specific and demonstrates an accuracy 45 times higher than general AI when answering scientific questions. This accuracy metric was achieved in a new study accompanying the funding announcement. Valence was trained on text processing and composition and function identification.

The method mimics the ability of an experienced chemist to distinguish between similar compositions and materials, as well as understand how minor changes can significantly impact an experiment. In chemistry, for instance, the slightest deviations in ingredients, procedures, or experimental conditions can lead to different results. Albert handles this through domain-specific intelligence and its Form Bench benchmark for formal chemistry.

Albert asserts that this benchmark will set a new standard for evaluation in this highly specialized field. The Albert platform combines scientific knowledge, AI tools, integrations, and regulatory control into a single environment. It allows scientists to interact with research data using natural language. By querying Albert, users coordinate tools, agents, and models to support complex scientific work.

The system helps teams find institutional knowledge and avoid repeating past experiments. It is capable of suggesting formula candidates, assisting in experiment design, and analyzing large datasets. These capabilities aim to eliminate bottlenecks in research and improve decision-making processes.

Furthermore, Albert supports enterprise requirements regarding data security and controlled access. Its chemistry-specific approach enables organizations to link information across various research systems, facilitating the discovery and reuse of valuable experimental knowledge.

Over the past year, Albert has demonstrated significant platform growth. Project creation increased 26-fold as Albert OS was implemented in organizational research functions. The number of scientists using the platform grew sixfold across 44 countries. These achievements reflect growing interest in specialized AI for corporate research.

Workflow creation also increased fourfold as more teams adopted various research processes on the platform. Ask Albert transformed from an AI search assistant into a broader R&D partner in just six months. Client feedback highlights the value of connecting disparate scientific information. Kenvue noted that the partnership with Albert improved connections within the overall data platform, while AkzoNobel used Ask Albert to query information covering raw materials and lab journal entries. Albert intends to use the new funding to expand its capabilities and accelerate product development.

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