Niantic Uses Pokémon Go Player Data To Build AI Navigation System
Niantic Uses Pokémon Go Player Data To Build AI Navigation System
Visual scans of the world have helped Niantic build what it calls a "Large Geospatial Model."
Last week, Niantic announced plans to create an AI model for navigating the physical world using scans collected from players of its mobile games, such as Pokémon Go, and from users of its Scaniverse app, reports 404 Media.
All AI models require training data. So far, companies have collected data from websites, YouTube videos, books, audio sources, and more, but this is perhaps the first we've heard of AI training data collected through a mobile gaming app.
"Over the past five years, Niantic has focused on building our Visual Positioning System (VPS), which uses a single image from a phone to determine its position and orientation using a 3D map built from people scanning interesting locations in our games and Scaniverse," Niantic wrote in a company blog post.
The company calls its creation a "large geospatial model" (LGM), drawing parallels to large language models (LLMs) like the kind that power ChatGPT. Whereas language models process text, Niantic's model will process physical spaces using geolocated images collected through its apps.
The scale of Niantic's data collection reveals the company's sizable presence in the AR space. The model draws from over 10 million scanned locations worldwide, with users capturing roughly 1 million new scans weekly through Pokémon Go and Scaniverse. These scans come from a pedestrian perspective, capturing areas inaccessible to cars and street-view cameras.
More about Niantic’s Large Geospatial Models on ARS Technica
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Physical AI Startup BrightAI Bootstraps To $80M In Revenue
BrightAI uses sensors and AI to help companies monitor physical infrastructure.
When Alex Hawkinson was the CEO of SmartThings, the consumer-focused connected devices company he co-founded and sold to Samsung for around $200 million, he kept thinking that Internet of Things (IoT) technology could probably solve bigger issues.
He left SmartThings in 2018 to figure out where connected devices could make the largest impact. He co-founded IoT company BrightAI, alongside Nathan Hanks, Douglas Burman, and Robert Parker, in 2019. When the pandemic hit in 2020, Hawkinson, now CEO, said that where BrightAI should focus became clear: infrastructure.
“In the pandemic, that downtime, sort of really made you think about what are the really important services that the modern life depends on? As you look at those, it’s sort of shocking how antiquated they are in many cases,” Hawkinson told TechCrunch.
More about using connected devices to fix critical infrastructure’s woes
Andrew Ng Explores The Rise Of AI Agents And Agentic Reasoning | BUILD
In recent years, the spotlight in AI has primarily been on large language models (LLMs) and emerging large multi-modal models (LMMs). Now, building on these tools, a new paradigm is emerging with the rise of AI agents and agentic reasoning, which are proving to be both cost-effective and powerful for building numerous new applications.
As AI continues to evolve, data across all industries—particularly unstructured data such as text, images, video, and audio—is becoming more critical than ever. In this keynote session from BUILD 2024, Andrews Ng, Founder and Executive Chairman of Landing AI, explores the rise of AI, agents, and the growing role of unstructured data. He also discusses how this convergence will shape automation and application building across industries.
Roboflow, Vision AI Startup, Raises $40 Million In Series B Funding Round
When I met Joseph Nelson, CEO and cofounder of Roboflow, I asked him a question that I ask pretty much everyone: If we randomly met at a party, how would you explain what your company does?
"I tell people that Roboflow makes developer tools to create a sense of visual understanding," Nelson told me. But, he added, depending on the person’s job, "I then will immediately jump to giving them an example that makes it real for them."
Then, for the next ten minutes, Nelson delighted in reeling off different professions and the corresponding visual use cases for Roboflow. For doctors, think medical imaging and diagnostics. Firefighters, how about early wildfire detection? If someone works in environmental research, Nelson points out that Roboflow is already being used to monitor coral reefs and underwater ecosystems. There are so many potential use cases for Roboflow, a computer vision startup, because the company deals in something so fundamental, even primal—what we see.
Roboflow has raised $40 million for its Series B, Fortune has exclusively learned. The round was led by GV, with Craft Ventures and Y Combinator joining along with Vercel’s Guillermo Rauch, Google's Jeff Dean, and Replit’s Amjad Masad. The company’s previous investors include Lachy Groom, Sam Altman, and Scott Belsky.
More about Roboflow’s raise and technology on Yahoo Finance
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We are now more connected than ever, but also more lonely. Could AI companionship be the cure? In this episode, Emily Chang explores the future tech behind a growing market of relationships-on-demand.
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Nvidia Boss Jensen Huang Predicts Computing Power Will Increase A 'Millionfold' In A Decade
Nvidia CEO Jensen Huang has said that the computing power driving advances in generative AI is projected to increase by "a millionfold" over the next decade.
In a special address on Monday, the billionaire chip boss told an industry conference in Atlanta that computing power was seeing a "fourfold" increase annually. This growth rate would see a vital resource of the AI boom become vastly more powerful within the next 10 years.
Nvidia has surged to become the world's most valuable company in the generative AI era. Companies across the tech sector have lined up to secure supplies of its specialist chips, known as GPUs, which offer the computing power needed to train smarter AI models.
Huang said that computing power was a key component of the so-called "scaling laws" that observe how AI large language models, or LLMs, see gains in performance as they grow in size and access more computing power and data. According to the Nvidia CEO, "scaling laws have shown predictable improvements in AI model performance."
Andrew Feldman, Cerebras Systems
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Thats all for today, however new advancements, investments, and partnerships are happening as you read this. AI is moving fast, subscribe today to stay informed.