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Shashank ND @shashankndToday we’re announcing Cent's $15M Series A, co-led by @BlumeVentures and @spc , and our acquisition of AI radiology platform Medsee. When you look at how healthcare works in India, almost all of it is organised around the moment someone falls ill. Hospitals, doctors and insurance are all paid to treat, and very little of the system is built to look for disease in people who feel well. It’s a big reason most cancers here are still found at stage 3 or 4. We started Cent to work on the other side of that problem. Over the last year, about 10,000 people have come to us without symptoms. 1 in 4 had something worth acting on, and 1 in 40 needed to see a doctor right away. Very few of them had any reason to suspect it. Finding disease this early, for millions of people, takes technology built for the purpose. This round lets us invest more deeply in our own hardware, AI and clinical research, and Medsee brings a strong AI reporting team into that work. Our goal is 10 million scans by 2035, and through them, helping save 1 million lives. Thank you to @BKartRed , @prateekmehta42 , Arun Sarin, @snsf , @sharathk83 , @krishna_srd and @AprameyaRadhaK for backing us, and to our team and every member who has trusted us with their health. Read more: @akhandelwal Arpit Garg
Aditya Agarwal @adityaag“The universe is really big, and almost none of it is inside computers.” When a problem is hard, make it bigger. @svlevine put a room full of robots in a repurposed Google conference room and had them grasp objects all day. It worked. Then it hit a wall: lots of experience, no prior knowledge. That wall became @physical_int. This conversation at @spc was awesome. I learned a lot! (00:28) From Video Games to Robotics: Sergey Levine's Journey (04:24) Founding Physical Intelligence: Why the Timing and Team Mattered (06:30) Inside Pi Zero: Building a Foundation Model for Robots (09:37) From Pi 0.5 to Pi 0.7: Teaching Robots to Reason and Generalize (16:45) What Makes a Great Robotics Researcher? (21:10) Solving Robotics' Data Problem and Building Learning Feedback Loops (28:04) The Future of Robotics: General-Purpose AI vs. Specialized Robots (33:24) World Models, Data Strategy, and Building a Robotics Research Culture
Baseten @basetenWith open models, we can build safety tooling directly into the inference layer. Our CEO and co-founder @tuhinone sat down with @kr00ney at @cnbc to discuss Project Beacon, and our work with @GoodfireAI to make safety the default for open intelligence.
Aditya Agarwal @adityaag“The universe is really big, and almost none of it is inside computers.” When a problem is hard, make it bigger. @svlevine put a room full of robots in a repurposed Google conference room and had them grasp objects all day. It worked. Then it hit a wall: lots of experience, no prior knowledge. That wall became @physical_int. This conversation at @spc was awesome. I learned a lot! (00:28) From Video Games to Robotics: Sergey Levine's Journey (04:24) Founding Physical Intelligence: Why the Timing and Team Mattered (06:30) Inside Pi Zero: Building a Foundation Model for Robots (09:37) From Pi 0.5 to Pi 0.7: Teaching Robots to Reason and Generalize (16:45) What Makes a Great Robotics Researcher? (21:10) Solving Robotics' Data Problem and Building Learning Feedback Loops (28:04) The Future of Robotics: General-Purpose AI vs. Specialized Robots (33:24) World Models, Data Strategy, and Building a Robotics Research Culture
Aditya Agarwal @adityaag“The universe is really big, and almost none of it is inside computers.” When a problem is hard, make it bigger. @svlevine put a room full of robots in a repurposed Google conference room and had them grasp objects all day. It worked. Then it hit a wall: lots of experience, no prior knowledge. That wall became @physical_int. This conversation at @spc was awesome. I learned a lot! (00:28) From Video Games to Robotics: Sergey Levine's Journey (04:24) Founding Physical Intelligence: Why the Timing and Team Mattered (06:30) Inside Pi Zero: Building a Foundation Model for Robots (09:37) From Pi 0.5 to Pi 0.7: Teaching Robots to Reason and Generalize (16:45) What Makes a Great Robotics Researcher? (21:10) Solving Robotics' Data Problem and Building Learning Feedback Loops (28:04) The Future of Robotics: General-Purpose AI vs. Specialized Robots (33:24) World Models, Data Strategy, and Building a Robotics Research Culture