SES AI Corp’s Post

When robots become artists, it's not just technology; it's a masterpiece in the making. #Adroittech #germany #german #likeforlike #followformore #reels #austria #uk #unitedkingdom #london #berlin #softwaredevelopment #german #ai #artificialintelligenceai #artificialintelligence #usa

 ⬅️🤖➡️ When robots move autonomously, they use SLAM – Simultaneous Localization and Mapping. Our colleagues Sebastian Scherer, 𝗣𝗲𝘁𝗲𝗿 𝗕𝗶𝗯𝗲𝗿 and Gerhard Kurz  from Bosch Research are working intensively on this technology and have highlighted the current state of research in a joint article. If you're interested in learning how robots navigate and the concepts of "Lifelong SLAM" & "Semantic SLAM," you can read the blog post here: https://lnkd.in/eCKby6d3 #BoschResearch #Blog #SLAM #Robots

A fascinating read. See if you can draw parallels to our situation with AI today.

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Following my previous post (about localization as the first fundamental problem in robotics) I want to talk about mapping as the second fundamental problem. Mapping refers to the way the environment is interpreted. When using robots, we expect that from such interpretation, there is going to be an interaction with the environment. Therefore the information gathered and processed should allow such interaction in a safe manner (from both points of view: no damages to the robot, no damages to the environment). The mapping process can be accomplished in several ways, but mapping depends intrinsically on the sensors used. Sensors like LiDARs (light detection and ranging) or cameras (any kind) are the most common sensors used, but the aim is to extract useful information. For example: if using a LiDAR, you might get cloud points. But unless you process the cloud point, it might be useless for the robotic application. Similar situation when using cameras: if you are just recording or taking pictures, the map will not be useful to the robot. One clear example of processing is detecting doors, so you can build a map of doors and label them as open/closed. Hence, the robot might use this info to decide whether to cross a door or not. But mapping is not a stand alone tool. It needs of localization in a variety of forms. When used with robots, it is often combined with dead-recknoning/odometry. In some cases, since mapping usually requires of data association (matching two or more sensor readings) then the outcome of such association is a localization estimate. Mapping is really a very challenging topic. If interested, take a look at the following DOIs (copy and paste on the browser) from some of my publications: 10.3390/s22083038, 10.1109/TITS.2020.2971054, 10.1016/j.cogsys.2019.03.018. If interested or any doubt, feel free to reach out. Cheers!

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Happy to share some scripts for those interested in NLP! I've been working with pre-trained Hugging Face LLMs to respond to a variety of tasks, including sentiment classification, customer question answering, text translation, and summarization. The diverse range of textual prompts ensure that your NLP needs are met efficiently and accurately. Stay ahead of the game with the cutting-edge technology! #NLP #HuggingFaceLLMs #TextualPrompts

Flying cars are on the horizon, expected to land in a neighborhood near you by late 2025 to early 2026. To those who doubt the reality of AI, what are your thoughts on this imminent development? The era of AI is no longer a distant future; with AI, the future is here and now. #FlyingCars #AI #FutureTech