Swiss robotics firm Anybotics has achieved a significant milestone by raising an additional $60 million, bringing its Series B round to a total of $110 million. This comes approximately 18 months after initially announcing the raising of a $50 million Series B. Spun out from the renowned ETH Zurich research university in 2016, Anybotics has developed a remarkable quadruped autonomous inspection robot known as Anymal, equipped with an array of sensors and cameras for the purpose of monitoring equipment in industrial settings. It can be utilized for various tasks such as tracking thermal anomalies as part of a preventive maintenance routine or detecting the presence of combustible gas.

Revolutionizing Industrial Inspections with Autonomous Robots

Company Background and Mission

Anybotics addresses the critical challenge of conducting routine inspections in complex and hazardous industrial environments. By automating these tasks, the company minimizes human exposure to dangerous or hard-to-reach areas. This leads to reduced downtime through more frequent inspections and higher coverage, as well as streamlined maintenance processes, ultimately resulting in higher productivity and operational reliability. In the 18 months since raising the first tranche of the Series B, the Zürich-based startup has witnessed a remarkable doubling of the number of units sold. Currently, close to 200 robots are deployed across diverse industries such as oil and gas, mining, power, utilities, and metals. Notable customers include Novelis (aluminum rolling and recycling), Iamgold (gold mining), Stelco (steel milling), and Stanford University, which employs Anybotics for advanced research purposes. "Our customers deploy anywhere from a single robot to fleets exceeding 10 robots, with the largest customer orders approaching 20 robots," explained Fankhauser. Fleet orders are becoming increasingly common as many of the company's industrial clients operate over 100 facilities globally, each with the potential to deploy multiple Anymal robots.

Anymal in Action and Its Impact

The capabilities of Anymal in real-world applications are truly remarkable. It can navigate through challenging industrial environments with ease, providing accurate and detailed inspection data. This helps industries ensure the safety and efficiency of their operations. For example, in the oil and gas industry, Anymal can detect potential leaks and other issues before they escalate into major problems, saving time and resources. In mining, it can access areas that are difficult for humans to reach, enabling more comprehensive inspections. The deployment of Anymal robots has led to significant improvements in maintenance processes and overall operational reliability.

Funding and Future Plans

Anybotics has now raised a total of $130 million since its inception. With the fresh $60 million in its coffers, the company is well-positioned to drive its U.S. expansion following the recent opening of its San Francisco office. It is notable that Anybotics has chosen to label this latest investment as an extension of the funding round that took place 18 months ago, rather than calling it a Series C. This decision is related to how the company plans to utilize the funds. The Series B extension focuses on scaling the core business globally, including expanding in the U.S. The Series C, on the other hand, will target broader growth by expanding the portfolio into new applications and industries. In other words, we can anticipate a significantly larger capital injection in the future, although it is not likely to occur before 2026. This Series B extension was co-led by new investors Qualcomm Ventures and Supernova Invest. A host of new and existing investors, including Bessemer Venture Partners, Nokia-backed NGP Capital, Swisscanto, Swisscom Ventures, TDK Ventures, and Walden Catalyst, also participated in the funding round.

AI training data indeed comes with a significant price tag, often making it accessible only to deep-pocketed tech firms. However, Harvard University is set to change this landscape. It plans to release a dataset comprising approximately 1 million public-domain books that span various genres, languages, and authors such as Dickens, Dante, and Shakespeare. These works are no longer protected by copyright due to their age.

Unlock the Potential of AI with Harvard's Dataset

Releasing the Dataset

The new dataset is yet to be made available, and the exact timing and release mechanism remain unclear. It contains books sourced from Google's long-running book-scanning project, Google Books. This indicates that Google will play a crucial role in making this "treasure trove" accessible far and wide. 1: The significance of this dataset lies in its vastness and diversity. It offers a wealth of literary content from different eras and cultures, providing researchers and AI developers with a unique opportunity to train their models on a comprehensive range of texts. This could lead to more accurate and contextually rich language models. 2: By making these public-domain books available, Harvard is not only contributing to the field of AI but also fulfilling its role in preserving and sharing cultural heritage. It allows for the exploration and utilization of literary works that might otherwise have remained hidden.

Leveling the Playing Field

Greg Leppert, the executive director of the IDI, emphasizes that the dataset is designed to "level the playing field." It opens up a huge amount of data to a wide range of entities, including research labs and AI startups. These organizations can now train their large language models (LLMs) using this extensive dataset. 1: This initiative has the potential to democratize AI development. Smaller entities that may not have the financial resources to acquire large datasets can now benefit from Harvard's contribution. It promotes innovation and competition in the AI space by providing equal access to valuable training data. 2: Moreover, by including financial backing from Microsoft and OpenAI, the IDI gains additional credibility and resources. This ensures the sustainability and growth of the project, enabling it to make a significant impact on the AI industry.

Implications and Future Prospects

The release of this dataset is expected to have far-reaching implications for the AI field. It could lead to the development of more advanced language models that better understand and generate human language. 1: As more researchers and developers have access to this diverse dataset, they can explore different approaches and techniques in AI training. This may lead to breakthroughs in areas such as natural language processing and machine translation. 2: In the future, we can expect to see a more diverse and inclusive ecosystem of AI development, with startups and research labs leveraging Harvard's dataset to create innovative applications. This could have a positive impact on various industries, including healthcare, finance, and entertainment.