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Category: robotics/AI

The Allen Institute for AI created the Open Language Model, or OLMo, which is an open-source large language model with the aim of advancing the science of language models through open research.

AI2 has partnered with organizations such as Surge AI and MosaicML for data and training code. These partnerships are crucial for providing the diverse datasets and sophisticated training methodologies that underpin OLMo’s capabilities. The collaboration with the Paul G. Allen School of Computer Science and Engineering at the University of Washington and Databricks Inc. has also been pivotal in realizing the OLMo project.

It is important to note that the current architecture of OLMo is not the same as the models that power chatbots or AI assistants, which use instruction-based models. However, that’s on the roadmap. According to AI2, there will be multiple enhancements made to the model in the future. In the coming months, there are plans to iterate on OLMo by introducing different model sizes, modalities, datasets, and capabilities into the OLMo family. This iterative process is aimed at continuously improving the model’s performance and utility for the research community.

OLMo’s open and transparent approach, along with its advanced capabilities and commitment to continuous improvement, make it a major milestone in the evolution of LLMs.

Continue reading “How OLMo From AI2 Redefines LLM Innovation” | >

In a famous line over 60 years ago, early AI pioneer Norbert Wiener summed up one of the core challenges that humanity faces in building artificial intelligence: If we use, to achieve our purposes, a mechanical agency with whose operation we cannot interfere effectively…we had better be quite sure…

The answer is a technology known as reinforcement learning from human feedback (RLHF).

RLHF has become the dominant method by which human developers control and steer the behavior of AI models, especially language models. It impacts how millions of people around the world experience artificial intelligence today. It is impossible to understand how today’s most advanced AI systems work without understanding RLHF.

At the same time, newer methods are quickly emerging that seek to improve upon and displace RLHF in the AI development process. The technological, commercial and societal implications are profound: at stake is how humans shape the way that AI behaves. Few areas of AI research are more active or important today.

Continue reading “What Is The Best Way To Control Today’s AI?” | >

The chatbot’s creators, from the AI company Limbic, set out to investigate whether AI could lower the barrier to care by helping patients access help more quickly and efficiently.

A new study, published today in Nature Medicine, evaluated the effect that the chatbot, called Limbic Access, had on referrals to the NHS Talking Therapies for Anxiety and Depression program, a series of evidence-based psychological therapies for adults experiencing anxiety disorders, depression, or both.

It examined data from 129,400 people visiting websites to refer themselves to 28 different NHS Talking Therapies services across England, half of which used the chatbot on their website and half of which used other data-collecting methods such as web forms. The number of referrals from services using the Limbic chatbot rose by 15% during the study’s three-month time period, compared with a 6% rise in referrals for the services that weren’t using it.

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Veteran autonomous delivery robot developer Starship Technologies announced it had raised an additional $90 million in funding to help expand its micro-logistics service to additional territories around the globe.

Starship Technologies was founded in 2014 by Skype co-founders Ahti Heinla and Janus Friis based on the idea that autonomy can help many of the challenges in last-mile deliveries. The company’s L4 autonomous delivery robots have completed over six million trips to date, transporting meals, packages, groceries, and important documents to students and other customers.

In August 2023, that mileage total was five million, operating in 30 different areas. Today, Starship’s robots have expanded to 80 locations worldwide, including the US, UK, Germany, Denmark, Estonia, and Finland.

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Sidewalk delivery robot services appear to be stalling left and right, but a pioneer in the concept says it is profitable and has now raised a round of funding to scale up to meet market demand. Starship Technologies, a startup out of Estonia that was an early mover in the delivery robotics space, has picked up $90 million in funding as it works to cement its position at the top of its category.

This latest investment round is being co-led by two previous backers: Plural, the VC with roots in Estonia and London that announced a new $430 million fund last month; and Iconical, the London-based investor backed by Janus Friis, the serial entrepreneur who was a co-founder of Skype, and who is also a co-founder of Starship itself.

It brings the total raised by Starship to $230 million, with previous backers including the Finnish-Japanese firm NordicNinja, the European Investment Bank, Morpheus Ventures and TDC.

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Read about NASA’s new instrument for landing on other worlds!

Landing on planetary bodies is both risky and hard, and landing humans is even riskier and harder. This is why technology needs to be developed to mitigate the risks associated with landing large spacecraft on the Moon and other planetary bodies we plan to continue exploring, both in the near and distant future. This is what makes the Nova-C lunar lander from Intuitive Machines—which is scheduled to launch to the Moon on February 13 and also called Nova-C (IM-1) —so vital to returning humans to the Moon. One of its NASA science payloads will be the Navigation Doppler Lidar (NDL), which will serve as a technology demonstration for future landers to help them navigate risky terrain and land safely.

Image of the Navigation Doppler Lidar which will be a technology demonstration during the IM-1 mission. (Credit: NASA/David C. Bowman)

When NASA was landing robots on Mars in the 1990s and 2000s, they discovered that radar and radio waves were insufficient for accurate landing measurements, so the engineers had to come up with their own plan to land spacecraft on extraterrestrial worlds.

Continue reading “Navigation Doppler Lidar: Revolutionizing Lunar Landing” | >