Verdict lists five of the top tweets on robotics in August 2022 based on data from GlobalData’s Technology Influencer Platform.
The top tweets are based on total engagements (likes and retweets) received on tweets from more than 378 robotics experts tracked by GlobalData’s Technology Influencer Platform during August 2022.
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The most popular tweets on robotics in August 2022: Top five
1. Massimo’s tweet on Know Barista’s coffee-making skills
Massimo, an engineer, shared an article on the built-in Eversys coffee machine from Switzerland being able to reproduce a perfect cup of latte art coffee like a professional latte artist in just 90 seconds. The movements and skills of latter artists are copied exactly with the help of an inBot OS intelligent learning system with integrated vision-guided robotic arms, motion control algorithms, and a perception and decision-making system, the article detailed.
The system also offered an intelligent demonstration and teaching system, a remotely operated monitoring system, and many artificial intelligence (AI)-enabled application programming interfaces (APIs). The inBot OS is now integrated into coffee-making and cooking robots with exceptional user experience, the article further noted. Know collaborated with the Danish company Universal Robots to build the two robotic arms that can achieve repeated positioning. The six turning joints allow the robotic arms to rotate 360 degrees and achieve the proficiency of latte artists in high precision tasks, such as frothing milk, and creating latte designs or art.
Username: Massimo
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By GlobalDataTwitter handle: @Rainmaker1973
Likes: 529
Retweets: 56
2. Vala Afshar’s tweet on the automatic EV charging robots
Vala Afshar, chief digital evangelist at the software development company Salesforce, shared a video on the electric vehicle (EV) charging system that dispatches a robot to the EV’s parking spot automatically to charge the car. The EV charging station ZiGGY provided on-demand services in parking facilities, the video demonstrated. Once a car arrived at its appointed location, the robot charger was ready to start the charging process.
The charging robots only required car owners to plug in the cable once the booking was confirmed for charging purposes. Once the EV was charged, ZiGGY informed the car owners and headed towards a new location or its home base, the video illustrated.
Username: Vala Afshar
Twitter handle: @ValaAfshar
Likes: 136
Retweets: 35
3. Ronald van Loon’s tweet on autonomous robots mitigating climate change effects
Ronald van Loon, CEO of the Intelligent World, an influencer network that connects businesses and experts to audiences, shared a video on autonomous robots and unmanned aerial technology gathering biodiversity data, which occurred in real time on Amazon’s, the e-commerce company’s on-demand cloud platform Amazon Web Services (AWS). As a result, Oxford University researchers were able to access data pipelines faster, the video highlighted. The video further detailed that AI and hyper-spectral image analysis could be further used on these data to collect more information with respect to biodiversity and climate change impacts.
Ecological communities were being disturbed as a result of these climate changes, the video further illustrated. This led to the loss of several species and thereby, an ensuing decline in biodiversity and the key ecosystem services they provided. The autonomous robots helped monitor, understand, and forecast changes in biodiversity that ultimately assisted in mitigating the effects of climate change.
Username: Ronald van Loon
Twitter handle: @Ronald_vanLoon
Likes: 75
Retweets: 36
4. Gary Marcus’s tweet on Google’s new PaLM-SayCan robot project
Gary Marcus, founder and CEO of the software development company Robust.AI, shared an article on the technology company Google, a subsidiary of Alphabet, building a robot on top of a language system that had such less understanding of the world could not be a success. Google’s new PaLM-SayCan robot project is attractive from a showmanship standpoint, but it only listens and acts in response to humans talking, Marcus added. Therefore, there were two key problems with the new robot project. Firstly, the new system relied on the language technology that was known to be problematic, and secondly, it was likely to be more problematic in the context of robots, the article detailed.
DeepMind, another subsidiary of Alphabet, further elaborated on 21 social and ethical problems of large language models, around topics such as data leaks, fairness, and information. Therefore, the PaLM-SayCan robot project was indicative of these problems requiring a fresh update, the article further noted. In addition, there was the problem of demos versus reality, Marcus stated. For instance, driverless car demos have existed for decades but reliability has been a challenge till now. As a result, Google planned to introduce them in 2017, but they are visible only in limited experimental tests in 2022, the article highlighted.
Username: Gary Marcus
Twitter handle: @GaryMarcus
Likes: 32
Retweets: 11
5. Spiros Margaris’s tweet on self-modelling robots
Spiros Margaris, venture capitalist and board member at the venture capital firm Margaris Ventures, shared an article on a Columbia Engineers robot having learned to imagine itself for the first time rather than the environment around it. Columbia Engineering revealed that they have built a robot that can learn a model of its whole body right from the beginning without any human assistance. The researchers described how their robot created a kinematic model of itself and how it used that model to plan movements, achieve goals, and avoid difficulties in different situations. The robot can also identify and repair any damage to its body, the article detailed.
Self-modelling robots reduce labour costs, while at the same time allowing it to maintain its own wear and tear, as well as identify and repair its own damage. Authors claim that this is an important ability, as there is an urgent need for autonomous systems to be more self-reliant, the article noted. For example, if a factory robot identified something not to be moving right, it would compensate or call for help.
Username: Spiros Margaris
Twitter handle: @SpirosMargaris
Likes: 24
Retweets: 31
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