{"id":3037,"date":"2023-06-14T16:40:28","date_gmt":"2023-06-14T16:40:28","guid":{"rendered":"https:\/\/salarydistribution.com\/machine-learning\/2023\/06\/14\/forged-in-flames-startup-fuses-generative-ai-computer-vision-to-fight-wildfires\/"},"modified":"2023-06-14T16:40:28","modified_gmt":"2023-06-14T16:40:28","slug":"forged-in-flames-startup-fuses-generative-ai-computer-vision-to-fight-wildfires","status":"publish","type":"post","link":"https:\/\/salarydistribution.com\/machine-learning\/2023\/06\/14\/forged-in-flames-startup-fuses-generative-ai-computer-vision-to-fight-wildfires\/","title":{"rendered":"Forged in Flames: Startup Fuses Generative AI, Computer Vision to Fight Wildfires"},"content":{"rendered":"
\n

When California skies turned orange in the wake of devastating wildfires, a startup fused computer vision and generative AI<\/a> to fight back.<\/p>\n

\u201cWith the 2020 wildfires, it became very personal, so we asked fire officials how we could help,\u201d said Emrah Gultekin, the Turkish-born CEO of Chooch, a Silicon Valley-based leader in computer vision.<\/p>\n

California utilities and fire services, they learned, were swamped with as many as 2,000 false positives a week from an existing wildfire detection system. The wrong predictions came from fog, rain and smudges on the lenses of a network of cameras they used.<\/p>\n

So, in a pilot project, Chooch linked its fire detection software to the camera network. It analyzed snapshots every 15 minutes, seeking signs of smoke or fire.<\/p>\n

Generative AI Sharpens Computer Vision<\/b><\/h2>\n

Then, the team led by Hakan Gultekin \u2014 Emrah\u2019s brother, a software wiz and Chooch\u2019s CTO \u2014 had an idea.<\/p>\n

They built a generative AI tool that automatically created descriptions of each image, helping reviewers discern when smoke is present. False positives dropped from 2,000 a week to eight.<\/p>\n

\"Startup<\/a>
Chooch detects smoke and fire despite bad weather or dirty camera lenses.<\/figcaption><\/figure>\n

\u201cFire chiefs were excited about launching the technology in their monitoring centers and what it could achieve,\u201d said Michael Liou, the president of Chooch, who detailed the project in a recent webinar<\/a>.<\/p>\n

Chooch\u2019s generative AI tool gives fire fighters in California\u2019s Kern County a dashboard on their smartphones and PCs, populated in real time with alerts, so they can detect wildfires fast.<\/p>\n

In 2020, California experienced 9,900 wildfires that burned 4.3 million acres of forest and caused $19 billion in losses. Stopping one fire from spreading out of control would pay for the wildfire detection system for 50 years, the company estimates.<\/p>\n

A Vision for Gen AI<\/b><\/h2>\n

Chooch\u2019s CEO says it\u2019s also the shape of things to come.<\/p>\n

\"Emrah<\/a>
Emrah Gultekin<\/figcaption><\/figure>\n

\u201cThe fusion of large language models<\/a> and computer vision will bring about even more powerful and accurate products that are easier to deploy,\u201d said Gultekin.<\/p>\n

For example, utilities can connect the software to drones and fixed cameras to detect corrosion on capacitors or vegetation encroaching on power lines.<\/p>\n

The technology could see further validation as Chooch enters an $11 million Xprize challenge<\/a> on detecting and fighting wildfires. Sponsors include PG&E and Lockheed Martin that\u2019s building an AI lab<\/a> to predict and respond to wildfires in a separate collaboration with NVIDIA.<\/p>\n

\"Startup<\/a>
Dashboards for PCs and smartphones can update firefighters with real-time alerts from Chooch\u2019s software.<\/figcaption><\/figure>\n

Chooch applies its technology to a host of challenges in manufacturing, retail and security.<\/p>\n

For example, one manufacturer uses Chooch\u2019s models to detect defects before products ship. Eliminating just 20% of the faults will pay for the system several times over.<\/p>\n

Inception of a Partnership<\/b><\/h2>\n

Back in 2019, a potential customer in the U.S. government asked for support with edge deployments it planned on NVIDIA GPUs. Chooch joined NVIDIA Inception<\/a>, a free program that nurtures cutting-edge startups.<\/p>\n

Using NGC<\/a>, NVIDIA\u2019s hub for accelerated software, Hakan was able to port Chooch\u2019s code to NVIDIA GPUs over a weekend. Now its products run on NVIDIA Jetson modules<\/a> and \u201chave been tested in the wild with full-motion video and multispectral data,\u201d Emrah said.<\/p>\n

Since then, the company rolled out support for GPUs in data centers and beyond. For example, the wildfire use case runs on NVIDIA A100 Tensor Core GPUs<\/a> in the cloud.<\/p>\n

Along the way, Chooch embraced software like Triton Inference Server<\/a> and the NVIDIA DeepStream<\/a> software development kit.<\/p>\n

\u201cThe combination of DeepStream and Triton increased our capacity 8x to run more video streams on more AI models \u2014 that\u2019s a huge win,\u201d Emrah said.<\/p>\n

A Wide Horizon<\/b><\/h2>\n

Now Chooch is expanding its horizons.<\/p>\n

The company is a member of the partner ecosystems for NVIDIA Metropolis<\/a> for intelligent video analytics and NVIDIA Clara Guardian<\/a>, edge AI software for smart hospitals. Chooch also works with NVIDIA\u2019s retail and telco teams.<\/p>\n

The software is opening new doors and expanding the use cases it can address.<\/p>\n

\u201cIt\u2019s hard work because there\u2019s so much uncharted territory, but that\u2019s also what makes it exciting,\u201d Emrah said.<\/p>\n

Learn more about <\/i>generative AI for enterprises<\/i><\/a>, and explore NVIDIA\u2019s solutions for <\/i>power grid modernization<\/i><\/a>.<\/i><\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

https:\/\/blogs.nvidia.com\/blog\/2023\/06\/14\/generative-ai-wildfires-chooch\/<\/p>\n","protected":false},"author":0,"featured_media":3038,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[3],"tags":[],"_links":{"self":[{"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/posts\/3037"}],"collection":[{"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/types\/post"}],"replies":[{"embeddable":true,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/comments?post=3037"}],"version-history":[{"count":0,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/posts\/3037\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/media\/3038"}],"wp:attachment":[{"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/media?parent=3037"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/categories?post=3037"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/salarydistribution.com\/machine-learning\/wp-json\/wp\/v2\/tags?post=3037"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}