AI News, Intel AI artificial intelligence

2020 CES: How Intel AI Helps the Red Cross Generate Open Source Maps for Disaster Relief

Maps are essential tools for the disaster relief worker —

To help give aid workers better maps, Kunce says some 600 volunteers came together, accessed satellite imagery and started adding details to OpenStreetMap (founded in 2004, it's like a Wikipedia for maps).

As the Ebola outbreak wound down, Kunce and three compatriots decided they need to fill the gaps caused by the lack of map data, which he says contributed in part to the length of the outbreak.

In the past five years, some 2,000 Missing Maps projects have put more than 200 million people on the map, based on buildings and residential areas added to OpenStreetMap.

Good satellite images are expensive, and differences in features like vegetation and building styles means an algorithm trained to identify details in one country or region won't apply accurately to another.

For the project announced this week at CES, the Intel-Red Cross team decided to map bridges in Uganda, a poorly mapped African country not only vulnerable to viral outbreaks (a case of Ebola emerged in June) but also prone to severe flooding.

The Intel team used the clean data to build the model, which then found 70 bridges in southern Uganda previously missed in both OpenStreetMap and the official Uganda Bureau of Statistics map —

First on the agenda, says Beale, is to open-source the training dataset “so other researchers or folks in humanitarian mapping can use it to experiment and develop models for similar problems.”

Longer-term solutions, Beale explains, could span from simply adapting the model to different locales all the way to using satellite and drone images taken immediately after a disaster to update maps automatically.

Instead of spending time digging through tourist brochures or having community members draw maps in the dirt, Red Cross volunteers can get right to executing those plans and help people in need —

The company's engineering expertise is helping address the world's greatest challenges as well as helping secure, power and connect billions of devices and the infrastructure of the smart, connected world –

Intel + Habana: What Does It Mean For AI (Artificial Intelligence)?

According Intel’s executive vice president and general manager of the Data Platforms Group, Navin Shenoy:“This acquisition advances our AI strategy, which is to provide customers with solutions to fit every performance need–from the intelligent edge to the data center.More specifically, Habana turbo-charges our AI offerings for the data center with a high-performance training processor family and a standards-based programming environment to address evolving AI workloads.” Already, Intel has seen traction with AI chips, bolstered with other acquisitions for companies like Nervana Systems and Movidius.For 2019, the expectation is that revenues will hit abut $3.5 billion for this segment, up 20% on a year-over-year basis.Intel also forecasts that the total addressable market will be greater than $25 billion by 2024 and half of this will be for the datacenter.

inference—has emerged and amassed a surprising number of startups looking to add their IP and approach into the mix.” Mukesh Khare, who is the vice president of IBM’s AI Hardware Research Center, agrees that AI chips are becoming more critical for AI: “Today, AI applications are being executed on systems designed for other, non-AI purposes.The rapid escalation in AI deployments is straining the capabilities of these systems, and expected overall improvements in general-purpose computing systems cannot keep up with this escalation in demand.For example, the compute needed for AI training is doubling every 3.5 months.To address this AI compute demand growth and opportunity, heterogeneous systems and AI accelerator chips, designed specifically and from scratch for AI, are required.” Note that there are many companies developing AI accelerator chips.

Artificial Intelligence Explained: Unleashing the Next Wave

Breaking down the difference between artificial intelligence, deep learning and machine learning.

Breakthrough Theory, AI in Action | AIDC 2018 | Intel AI

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Dr. Naveen Rao reveals the industry tailwinds pushing Intel's diverse AI hardware and software portfolio into the spotlight, featuring new performance numbers ...

Intel's neuron-based AI chips could drive a car

Tests suggest they use 100-times less energy on certain machine learning tasks. Read more: ...

Genomics Sequencing: Fighting Disease With Artificial Intelligence | Intel

When Bryce Olson was diagnosed with advanced prostate cancer, he sequenced the DNA of his tumor and opened doors to new treatment options for his ...

Artificial Intelligence and Intel® Xeon® Scalable Processors | Intel Business

Artificial Intelligence is impacting every industry. As it becomes pervasive, Intel is helping customers move, store, and process data to get their AI models into ...

Intel Nervana Artificial Intelligence 1/31/17

Presentation Details: Title: Hands-on Deep Learning Workshop Abstract: Deep learning is unlocking tremendous economic value across various market sectors.