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Be it Agility Robotics’ bots lifting weights to Google DeepMind’s playing football, we have seen tech companies heavily training and working on improving a robot’s capabilities. In a run towards improving task performance, companies are constantly innovating in the field.
However, compared to the growth of LLM models, advancements in robotics would take time, as it deals with imperfections of control and sensors in the real world. Building and testing these prototypes often get delayed. And while an LLM’s prowess is measured by the training datasets and tokens, a robot’s efficiency is gauged by the number of tasks it can accomplish — something that takes years to master.
Drawing parallels to how GPT was built and improved by an ecosystem of companies that worked together, data expert and AI strategy advisor Vin Vashishta recently spoke about how robotics is still on the path to having its own GPT moment.
He believes that innovation doesn’t start with advanced robotics, instead with applied robotics and an ecosystem of companies working together. With tech companies working and investing in robotics companies, their next big breakthrough will probably happen with companies being able to build on small-scale demonstrations and development of fundamental data collection components.
So, there are two pertinent questions — how far have tech companies gone in robotics development and will the turning point occur any time soon?
Waiting for the GPT-Moment
The sector, as a whole, is continuously innovating, and yet, the breakthrough that everyone is anticipating is yet to come. This can be attributed to the fact that robotics, as a sector, is extremely hard to get right. It’s hard to make the systems robust and repeatable at scale. Moreover, robotics is a tricky sector for investors as huge money is required to bring production to scale. This discourages investors who are looking to make quick money.
Recently, AIM got in touch with Gokul NA, founder of CynLr: Cybernetics Laboratory, a robotics company that works on robotic arms. He spoke about the time taken in robotics training. “It might be easy to teach a robotic arm to take something from one position to another, but it takes over two years to get a successful robotic arm application, if feasible at all.”
Gokul also spoke about the future of this field. “We have seen the data revolution, and it’s time to see the object revolution at this point. We see bright possibilities for this industry and it is left to us to figure out how we can leverage it and make it a success.”
According to a recent report, the global robotics market size was valued at $12.1 billion in 2020, and is expected to reach $150 billion by 2030. One of the biggest use cases for robotics is in warehouses, where the need for automation is huge, creating room for growth. Other industries such as construction, agriculture, and healthcare are also sectors where robotics work.
Big Tech Goes the Robotics Way
Companies are taking leaps to invest in robotics companies. You even have major tech players, such as Google, Microsoft, OpenAI, and Tesla, which have invested in it, and continue to do so. In spite of scrapping their in-house robotics division in 2021, OpenAI recently invested in a Norway-based robotics startup, 1x, that builds humanoid robots capable of human-like movements and behaviours.
A few weeks ago, AMP Robotics, a Colorado-based startup that creates robotic systems, received close to $100 million from Microsoft’s Climate Innovation Fund.
Last week, Canadian AI and robotics company SanctuaryAI unveiled their advanced general-purpose robot called Phoenix. The company claims to have developed the world’s first humanoid general-purpose robot powered by Carbon, which is a unique AI control system.
Last year, Tesla revealed their humanoid robot Optimus. It received a lukewarm response, and even garnered criticism. Gary Marcus raised concerns about why Tesla would build such a robot with no clear direction on what the real-world applications are. Snubbing the critiques, the companies are continuously investing in this sector, awaiting the ‘GPT moment’ for robotics.
