Chef Robotics

Key players in the AI in food and beverages market have strengthened their market presence through product launches. These initiatives serve as vital tools for enhancing market penetration and strengthening their competitive edge within the industry. Follow Grand View Research, Inc to stay ahead of the curve. Learn more @ https://lnkd.in/dXxaPU8f #GVR #technology #AI #aiinfood #foodandbeverage #aiinfnb #artificialintelligence

Happy to share that I've started a new chapter with Chef Robotics! I’m really looking forward to being part of a team that’s pushing the boundaries in automation and transforming food production with cutting-edge robotics. I also want to take a moment to thank Dusty Robotics for the opportunity to break into the robotics industry. Special shoutout to Tessa Lau, Erroin Martin, Nicole Spicer, and the entire team for welcoming me aboard. While my time there was brief, it was a great experience, and I’m grateful for everything I learned and the connections I made. Looking forward to this next adventure! 🚀

🎉 Big news! The official calendar of events for #SFTechWeek and #LATechWeek is now LIVE! And thrilled to announce that this is officially our BIGGEST Tech Week, ever! - 850+ events 🤯 - San Francisco: Oct 7-13 🌉 - Los Angeles: Oct 14-20 🌴 Link to register below to see all events👇 Sneak peek of a few events you can't miss... - The Future of Entertainment with Andrew Chen (a16z), Carter Reum (M13), Jeffrey Evans (Mantis), David Sabow (HSBC) - Founder Fireside Chat with Chris Best, Substack Founder & CEO - Game Changers: Breakfast with Fenwick and a16z with Jonathan Lai (a16z GP) and Kat Duncan (Partner, Fenwick) - How Design, Story, and AI are Changing Software with Siqi Chen, CEO of Runway - AI Breakthrough: Finding Product-Market Fit with executives from Mistral AI, Pinecone, Anyscale, HSBC and a16z - SPEEDRUN Demo Day by A16Z GAMES 40%+ of the events self-report having an AI theme. We're also seeing a ton of diversity in topics, including: B2B, fundraising/investing, fintech, engineering, deeptech, infra, consumer, games, media/entertainment, SaaS... In just 2 years, the Tech Week community has grown to 100k+ folks and has evolved from primarily VC deal flow to deal flow AND a diverse range of use cases: - B2B Lead Generation - Product Launches - Sourcing Talent - Meeting Investors / Fundraising - Brand Building It's been amazing to see Tech Week serve as a bridge between different cities, connecting the SF, LA, and NY ecosystems. Our back-to-back scheduling for SF and LA is designed to encourage cross-pollination. 🐝Tech Week wouldn’t be possible without incredible partners. Thank you to Andreessen Horowitz Fenwick & West, HSBC Innovation Banking, Dialpad, Stripe, Atlassian, PwC, and Nasdaq for your support and belief in the mission 🙏 And Tech Week would not be possible without the incredible (and growing!) team behind it - huge shoutout to Andrew Chen Rose Johnson Shrikala Kashyap Joung Lee for your dedication to the community 😊 Make sure you're following us at TECH WEEK by a16z for more updates, and register at tech-week.com!

Rajat Bhageria, Founder & CEO, Chef Robotics joined Grayson Brulte on The Road to Autonomy podcast to discuss the future of automation in the food industry amidst the backdrop of increasing labor shortages. Chef is addressing the critical labor shortage in the food industry that is being driven by higher labor costs and increased turnover through automation. 🎧 Listen on Apple Podcasts: https://lnkd.in/dsXVKBGV 🎧 Listen/Watch on Spotify: https://lnkd.in/diuJ7BBa 🎥 Watch on X: https://lnkd.in/dDZRbgvu 🎥 Watch on YouTube: https://lnkd.in/drcB85bi #RoadToAutonomy #AutonomyEconomy #Automation #QSR #FoodIndustry #Labor

Chef systems use computer vision and the relevant AI policy to figure out where to pick ingredients from. This animation is a good demonstration of this process. The system scans a hotel pan filled with food to gauge volume and topography; based on the topography, the AI policy for the relevant ingredient, the utensil being used (and the expected sweep of volume based on pick pose), the model recommends a pick pose. Then the system plans a path to that pose and executes a pick. This allows Chef to pick at whatever portion size the customer wants and also be very consistent.

These robots will replace the most mundane tasks, such as scooping food in a tray, which should ideally be automated. Check out the video to see how Rajat Bhageria's company, Chef Robotics, is innovating and solving a massive problem in the food industry.

Chef uses AI to discern where to pick ingredients from and where to place them. The more data our AI models ingest, the better their performance becomes. This video is a good visual demonstration of how our software works! On a high level - To pick, our models take into consideration the AI policy for that ingredient class, the topography of the food it's picking from, any occlusions and a memory map of past picks, as well as the utensil the robot is using (and the correlated expected sweep volume from picking) to figure out the optimal pick pose. After it picks, Chef will use a 1 gram resolution scale and some signal processing to figure out how much weight was actually picked. Once we have this, we'll see how close our AI policy was to the target weight; based on this, it'll adjust how it picks the next pick. - To place, another model will detect and track the trays (along with estimating speed) as they move down the line. This model will react to things like changes in tray orientation, distances of the tray from the robot, skew in the conveyor from the robot, slope of the conveyor, conveyor stops, changes in conveyor velocities and accelerations, and any last minute additions or removals of trays that can affect tray tracks. All of this allows Chef to place food into a tray the way the customers wants - e.g., into a particular compartment, spread over the tray, or in a particular part of the tray while minimizing spillage.

Placing small portions of ingredients accurately can be a challenge. In this video, Chef is consistently picking chives at 0.5 grams and then placing them onto a tray while spreading them. Through AI policies per ingredient class and a library of utensils, Chef systems can pick and plate ingredient servings of any size ranging from small portions of toppings like herbs, to moderate portions of things like sauces, to larger portions of main meal components like grains, proteins and vegetables. AI + Robotics are accelerating fast!