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Intel touts latest Xeon processor for scaling 5G networks

April 6, 2021 Big Data

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Intel launched its latest datacenter platform in the form of the 3rd Gen Intel Xeon Scalable processors.

The Santa Clara, California-based chipmaker said that the processors deliver a 46% performance increase on datacenter workloads. The server chips with integrated AI will power cloud-native datacenters and applications such as 5G networks, cryptography, drug discovery, and confidential computing. For 5G, the new chips deliver on average 62% more performance on network and 5G workloads.

In an online briefing, Intel executive vice president Navin Shenoy said Intel has added advanced security with Intel Software Guard Extension and Intel Crypto Acceleration. Intel has shipped more than 200,000 chips for revenue in the first quarter, and it boasts more than 250 design wins for the chips with 50 partners, 15 telecom equipment and communications firms, and 20 high-performance computing labs.

AT&T said it is seeing 1.9 times higher throughput and 33% more memory capacity with the combination of the Intel Xeon Scalable processors and Intel Optane Persistent Memory, so the network can serve the same number of subscribers at higher resolution or a greater number of subscribers at the same resolution. Verizon and Vodafone also said they’re using the new Xeons. With the chips, Intel said communication service providers can increase 5G user plane function performance by up to 42%.

The chip uses Intel’s 10-nanometer manufacturing process (equivalent to the 7-nanometer process of rivals based on nomenclature), and it delivers up to 40 cores per processor and up to 2.65 times higher average performance gain compared to five-year-old systems.

Intel CEO Pat Gelsinger said in an online briefing that over the past year companies have been forced to undertake a warp-speed cloudification of infrastructure to serve remote workforces, and he said the new processors have flexible architecture for advanced security and built-in AI to handle processing from the edge to the cloud.

“Technology is like magic,” he said. “It has the power to improve the lives of every person on the planet. It’s a new day at Intel. We are no longer just the CPU company.”

Intel touts latest Xeon processor for scaling 5G networks

Above: Intel Xeon

Image Credit: Intel

He said Intel combines software, silicon, and manufacturing to differentiate itself from rivals. The company will operate internal factories, strategically use foundry services to make Intel chips with the help of outside contract manufacturers, and offer its own foundry services to others.

“With a backdrop of fierce competition, Intel is leading with its strengths with its 3rd Gen Xeon processors,” said Patrick Moorhead, an analyst at Moor Insights & Strategy, in a message to VentureBeat. “The company is offering a platform approach to provide its partners solutions incorporating CPUs, storage, memory, FPGAs, and networking ASICs. This is in addition to its ability to leverage resources for co-marketing and co-development. I also believe the company is differentiated with its on-chip ML inference and cryptographic capabilities versus its closest competitors.”

The latest hardware and software optimizations deliver 74% faster AI performance compared with the prior generation and provide up to 1.5 times higher performance across a broad mix of 20 popular AI workloads versus AMD Epyc 7763 and up to 1.3 times higher performance on a broad mix of 20 popular AI workloads versus Nvidia A100 GPU, Intel said.

Above: Intel CEO Pat Gelsinger touts the latest Intel Xeon Scalable processors.

Shenoy said its security-focused SGX protects sensitive code and data with the smallest potential attack surface within the system. It is now available on two-socket Xeon Scalable processors with enclaves that can isolate and process up to a terabyte of code and data to support the demands of mainstream workloads.

And Shenoy said Intel Crypto Acceleration delivers performance across a variety of important cryptographic algorithms. Businesses that run encryption-intensive workloads, such as online retailers who process millions of customer transactions per day, can leverage this protection without impacting user response times or overall system performance.

Intel said that more than 800 of the world’s cloud service providers run on Intel Xeon Scalable processors, and all of the largest cloud service providers are planning to offer cloud services in 2021 powered by the newest chips. HP Enterprise said it has launched new computers across eight different models with the new Xeons, and it uses AMD’s latest Epyc processors as well.

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Big Data – VentureBeat

Intel Geospatial is a cloud platform for AI-powered imagery analytics

October 28, 2020 Big Data

Intel today quietly launched Intel Geospatial, a cloud platform that features data engineering solutions, 3D visualizations, and basic analytics tools for geovisual workloads. Intel says it’s designed to provide access to 2D and 3D geospatial data and apps through an ecosystem of partners, addressing use cases like vegetation management, fire risk assessment and inspection, and more.

The geospatial analytics market is large and growing, with a recent Markets and Markets report estimating it will be worth $ 96.34 billion by 2025. Geospatial imagery can help companies manage assets, for example network assets prone to damage during powerful storms. Moreover, satellite imagery and the AI algorithms trained to analyze it have applications in weather prediction, defense, transportation, insurance, and even health care, namely because of their ability to capture and model environments over extended periods of time.

Using Intel Geospatial, which is powered by Intel datacenters, customers can ingest and manage geovisual data from a mobile- and desktop-accessible web portal. They’re able to view slope, elevation, and other data layers in a 3D environment with zoom, pan, and tilt controls and auto-updated time and date stamps. Moreover, they can analyze the state of various target assets as well as run analytics to extract insights that can then be passed to existing enterprise systems.

Intel Geospatial offers data from satellites, manned aircraft, and unmanned aerial vehicles (UAVs) like drones, with data from Mobileye — Intel’s autonomous vehicle subsidiary — available upon request. The platform’s user interface auto-populates with area-specific datasets and allows for search based on street addresses or GPS coordinates, which are standardized for analytics.

Intel Geospatial offers out-of-the-box algorithms for risk classification, object counting, distance measuring, and public and private record reconciliation. Intel says it’s leveraging startup Enview’s AI to power 3D geospatial classification for faster lidar analytics turnaround. Meanwhile, LiveEO is delivering algorithmic monitoring for railway, electricity, and pipelines.

Intel’s new service joins the list of geospatial products already offered by companies including Google, Microsoft, and Amazon. Google’s BigQuery GIS lets Google Cloud Platform customers analyze and visualize geospatial data in BigQuery. Microsoft offers Azure Maps, a set of geospatial APIs to add spatial analytics and mobility solutions to apps. Amazon provides a registry of open geospatial datasets on Amazon Web Services. And Here Technologies, the company behind a popular location and navigation platform, has a service called XYZ that enables anyone to upload their geospatial data — such as points, lines, polygons, and related metadata — and create apps equipped with real-time maps.

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AMD is buying Xilinx for $35 billion to compete with Intel in the datacenter

October 27, 2020 Big Data

Processor and graphics firm Advanced Micro Devices has agreed to buy programmable chip maker Xilinx for $ 35 billion in stock. AMD also reported better-than-expected third-quarter earnings and raised its forecast for fourth-quarter results.

The acquisition will help AMD stay competitive with archrival Intel in the datacenter, where programmable chips have become increasingly popular. It also follows a trend for increasing consolidation in the chip industry, where Nvidia is acquiring Arm for $ 40 billion. (Intel bought Xilinx’s rival in programmable chips, Altera, for $ 16.7 billion in 2015).

AMD reported third-quarter adjusted earnings per share of 41 cents on revenue of $ 2.8 billion, up from 18 cents and $ 1.8 billion for the same quarter a year earlier. Analysts had expected 35 cents per share in earnings and $ 2.56 billion in revenues.

Shares of AMD fell 3.5% in trading on Tuesday morning, while shares of Xilinx rose 9%. That pattern is typical in acquisition deals.

“Our acquisition of Xilinx marks the next leg in our journey to establish AMD as the industry’s high performance computing leader and partner of choice for the largest and most important technology companies in the world,” said Lisa Su, CEO of AMD, in a statement. “This is truly a compelling combination that will create significant value for all stakeholders, including AMD and Xilinx shareholders who will benefit from the future growth and upside potential of the combined company. The Xilinx team is one of the strongest in the industry and we are thrilled to welcome them to the AMD family. By combining our world-class engineering teams and deep domain expertise, we will create an industry leader with the vision, talent and scale to define the future of high performance computing.”

AMD is buying Xilinx for $35 billion to compete with Intel in the datacenter

Above: Xilinx’s Zynq programmable chips are used in the Subaru Levorg.

Image Credit: Xilinx

Xilinx shareholders will get 1.7234 shares of AMD common stock for each share of Xilinx common stock that they own. That amounts to $ 143 a share for Xilinx stock, which has been trading under $ 125. While AMD has a lot less cash than rival Intel, its stock price has had a big run as it gained market share during the past couple of years with its Zen and Zen 2 chip designs. AMD’s stock price has tripled since the spring of 2018.

This quarter, AMD is shipping its next-generation server chips, code-named Milan, to cloud customers. Xilinx is in the midst of a product renewal with its programmable Versal ACAP chips, which help datacenters deal with with a tsunami of computing demands from artificial intelligence.

Over time, AMD expects to save $ 300 million via streamlining costs in the first 18 months after the approval of the acquisition. That may mean lower costs through layoffs, but the company didn’t spell that out. AMD expects the deal will close by the end of 2021.

“AMD’s intent to acquire Xilinx is a bold move that I think makes sense and caps off an incredible run by AMD,” said Patrick Moorhead, an analyst at Moor Insights & Strategy, in an email to VentureBeat. “I believe AMD will continue to organically grow with or without this acquisition, as hopefully evidenced by its monster Q3, its upward guide, and roadmap.”

He added, “I do think AMD has a brighter, long-term future with Xilinx as it creates a larger entity that is more diversified across different markets and products while leveraging similar technologies. While I was more excited by its long-term possibilities, I am now equally impressed by its day one accretion and look forward to getting more details on its short-term leverage.”

For the third quarter, AMD reported $ 1.67 billion in revenue from computing and graphics, up 31% from a year earlier. It reported $ 1.13 billion in revenue for its enterprise, embedded, and semi-custom chip division. That’s up 116%, in part because AMD is supplying chips to the Microsoft and Sony game consoles launching in November.

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Intel revenues drop 4% to $18.3 billion for Q3 2020 as competition heats up

October 23, 2020 Big Data

Intel reported earnings that matched Wall Street’s expectations during what was another tumultuous quarter for the world economy.

For the third quarter ended September 30, the big PC chipmaker posted non-GAAP earnings per share (EPS) of $ 1.11 a share on revenue of $ 18.3 billion, compared with non-GAAP EPS of $ 1.42 a share on revenue of $ 19.2 billion a year earlier.

CEO Bob Swan described the results as “solid” and said they exceeded Intel’s own expectations “despite pandemic-related impacts in significant portions of the business.”

Intel’s shares are down 8% this year, and the company’s market value at $ 229.2 billion remains lower than its biggest U.S. rival, Nvidia, which is valued at $ 330.1 billion. Intel’s stock price declined 10% to $ 48.30 a share in after-hours trading, as a number of the company’s business lines were weak. Intel faces tough competition from Nvidia in AI and graphics chips, while Advanced Micro Devices is much more competitive in central processing units (CPUs).

Analysts expected Intel to post adjusted earnings of $ 1.11 a share, down from $ 1.42 a share reported a year ago. Revenue was expected to be $ 18.24 billion, down from $ 19.19 billion a year ago.

“Nine months into 2020, we’re forecasting growth and another record year, even as we manage through massive demand shifts and economic uncertainty,” Swan said in a statement. “We remain confident in our strategy and the long-term value we’ll create as we deliver leadership products and aim to win share in a diversified market fueled by data and the rise of AI, 5G networks and edge computing.”

Intel revenues drop 4% to $18.3 billion for Q3 2020 as competition heats up

Above: Intel has some new Core processors coming in Q1 2021.

Image Credit: Intel

In July, Intel made the embarrassing disclosure that its new generation of 7-nanometer manufacturing has been delayed. This prompted Intel to say it was considering outsourcing some manufacturing to a contract chip manufacturer.

One of Intel’s advantages has been its internal manufacturing with plants in the United States, but the company has stumbled twice now on transitions to new generations, allowing rivals who use external manufacturer TSMC and others to make gains on Intel. Intel will likely offer an update on the manufacturing in its earnings call.

And Intel announced this week it would sell most of its flash memory business to SK Hynix for $ 9 billion. Intel’s memory business has been a mixed one with losses over a number of years.

“This is the first quarter I have seen COVID-19 negatively impact the company,” said Patrick Moorhead, an analyst at Moor Insights & Strategy. “Also, I believe it sold more 10nm parts with a faster ramp which are more costly to manufacture initially than 14nm parts. COVID-19 appears to have impacted the mix as PC demand shifted to lower margin education [PCs] and enterprise/datacenter demand looks to have dried up, replaced or weighed down by lower-margin cloud business. I do think [the CPU codenamed] Tiger Lake is strong for thin and light notebooks and believe it has a very good assortment coming into the holidays.

He added, “Looking at the longer-term picture, I do believe CEO Bob Swan is focusing (AI, GPUS, networking) and disinvesting (NAND, modems) in the right things in growing markets. I don’t think Intel needs to apologize for anything at this point. Its stock is trading at 10 times earnings and looks cheap.”

Swan said the company is raising its full-year revenue and earnings expectations from its July guidance. It now expects 5% revenue growth in 2020, with the full-year number coming in at $ 75.3 billion, while non-GAAP EPS will be $ 4.90 a share.

To date, Intel has generated $ 25.5 billion in cash from operations. Of Intel’s groups, Mobileye was up 2% at $ 234 million, and the PC client group was up 1% at $ 9.8 billion compared to a year ago. But Intel’s other four groups were down.

The datacenter group came in at $ 5.9 billion, down 7% from a year ago. The internet of things group was down 33% at $ 677 million. The NSG memory group was down 11% at $ 1.2 billion, and the programmable solutions group was down 19% at $ 411 million.

Intel said that continued strength in laptop sales was offset by COVID-19 headwinds affecting parts of the business. Cloud revenue grew 15% from a year ago with demand for supporting work-from-home environments, but the weaker economy affected enterprise and government sales, which was down 47% after two quarters of 30% growth.

The pandemic also hurt the internet of things and memory groups. Mobileye returned to growth as vehicle production recovered. Intel said more than 150 designs are in the works for new laptops with Intel processors.

For the fourth quarter, Intel expects non-GAAP earnings per share of $ 1.10 a share on revenue of $ 17.4 billion.

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Intel inks agreement with Sandia National Laboratories to explore neuromorphic computing

October 2, 2020 Big Data

As a part of the U.S. Department of Energy’s Advanced Scientific Computing Research program, Intel today inked a three-year agreement with Sandia National Laboratories to explore the value of neuromorphic computing for scaled-up AI problems. Sandia will kick off its work using the 50-million-neuron Loihi-based system recently delivered to its facility in Albuquerque, New Mexico. As the collaboration progresses, Intel says the labs will receive systems built on the company’s next-generation neuromorphic architecture.

Along with Intel, researchers at IBM, HP, MIT, Purdue, and Stanford hope to leverage neuromorphic computing — circuits that mimic the nervous system’s biology — to develop supercomputers 1,000 times more powerful than any today. Chips like Loihi excel at constraint satisfaction problems, which require evaluating a large number of potential solutions to identify the one or few that satisfy specific constraints. They’ve also been shown to rapidly identify the shortest paths in graphs and perform approximate image searches, as well as mathematically optimizing specific objectives over time in real-world optimization problems.

Intel’s 14-nanometer Loihi chip contains over 2 billion transistors, 130,000 artificial neurons, and 130 million synapses. Uniquely, the chip features a programmable microcode engine for on-die training of asynchronous spiking neural networks (SNNs), or AI models that incorporate time into their operating model such that the components of the model don’t process input data simultaneously. Loihi processes information up to 1,000 times faster and 10,000 more efficiently than traditional processors, and it can solve certain types of optimization problems with gains in speed and energy efficiency greater than three orders of magnitude, according to Intel. Moreover, Loihi maintains real-time performance results and uses only 30% more power when scaled up 50 times, whereas traditional hardware uses 500% more power to do the same.

Intel and Sandia hope to apply neuromorphic computing to workloads in scientific computing, counterproliferation, counterterrorism, energy, and national security. Using neuromorphic research systems in-house, Sandia plans to evaluate the scaling of a range of spiking neural network workloads, including physics modeling, graph analytics, and large-scale deep networks. The labs will run tasks on the 50-million-neuron Loihi-based system and evaluate the initial results. This will lay the groundwork for later-phase collaboration expected to include the delivery of Intel’s largest neuromorphic research system to date, which the company claims could exceed more than 1 billion neurons in computational capacity.

Earlier this year, Intel announced the general readiness of Pohoiki Springs, a powerful self-contained neuromorphic system that’s about the size of five standard servers. The company made the system available to members of the Intel Neuromorphic Research Community via the cloud using Intel’s Nx SDK and community-contributed software components, providing a tool to scale up research and explore ways to accelerate workloads that run slowly on today’s conventional architectures.

Intel claims Pohoiki Springs, which was announced in July 2019, is similar in neural capacity to the brain of a small mammal, with 768 Loihi chips and 100 million neurons spread across 24 Arria10 FPGA Nahuku expansion boards (containing 32 chips each) that operate at under 500 watts. This is ostensibly a step on the path to supporting larger and more sophisticated neuromorphic workloads. Intel recently demonstrated that the chips can be used to “teach” an AI model to distinguish between 10 different scents, control a robotic assistive arm for wheelchairs, and power touch-sensing robotic “skin.”

In somewhat related news, Intel today announced it has entered into an agreement with the U.S. Department of Energy to develop novel semiconductor technologies and manufacturing processes. In collaboration with Argonne National Laboratory, the company will focus on the development and design of next-generation microelectronics technologies such as exascale, neuromorphic, and quantum computing.

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Intel details chips designed for IoT and edge workloads

September 23, 2020 Big Data

Intel today announced the launch of new products tailored to edge computing scenarios like digital signage, interactive kiosks, medical devices, and health care service robots. The 11th Gen Intel Core Processors, Atom x6000E Series, Pentium, Celeron N, and J Series bring new AI security, functional safety, and real-time capabilities to edge customers, the chipmaker says, laying the groundwork for innovative future applications.

Intel expects that the edge market to be a $ 65 billion silicon opportunity by 2024. The company’s own revenue in the space grew more than 20% to $ 9.5 billion in 2018. And according to a 2020 IDC report, up to 70% of all enterprises will process data at the edge within three years. To date, Intel claims to have cultivated an ecosystem of more than 1,200 partners, including Accenture, Bosch, ExxonMobil, Philips, Verizon, and Viewsonic, with over 15,000 end customer deployments across “nearly every industry.”

The 11th Gen Core processors — which Intel previewed in early September — are enhanced for internet of things (IoT) use cases requiring high-speed processing, computer vision, and low-latency deterministic processing, the company says. They bring an up to 23% performance gain in single-threaded workloads, a 19% performance gain in multithreaded workloads, and an up to 2.95 times performance gain in graphics workloads versus the previous generation. New dual video decode boxes allow the processors to ingest up to 40 simultaneous video streams at 1080p up to 30 frames per second and output four channels of 4K or two channels of 8K video.

According to Intel, the combination of the 11th Gen’s SuperFin process improvements, miscellaneous architectural enhancements, and Intel’s OpenVINO software optimizations translates to 50% faster inferences per second compared with the previous 8th Gen processor using CPU mode or up to 90% faster inferences using the processors’ GPU-accelerated mode. (Intel says the 11th Gen Core i5 is up to twice as fast in terms of inferences per second as an 8th Gen Core i5-8500 when running on just the CPU in each product.) AI inferencing algorithms can run on up to 96 graphic execution units (INT8) or run on the CPU with VNNI built in, an x86 extension that’s part of Intel’s AVX-512 processor instruction set for accelerating convolutional neural network-based algorithms.

As for the Atom x6000E Series, Pentium, Celeron N, and J Series, Intel says they represent its first processor platform specifically enhanced for IoT. All four deliver up to 2 times better graphics performance, a dedicated real-time offload engine, enhanced I/O and storage, and the Intel Programmable Services Engine, which brings out-of-band and in-band remote device management. They also support 2.5GbE time-sensitive networking components and resolutions up to 4K at 60 frames per second on upwards of three displays, and they meet baseline safety requirements with built-in hardware-based security.

Intel says it already has 90 partners committed to delivering 11th Gen Core solutions and up to 100 partners locked in for the Intel Atom x6000E Series, Intel Pentium, Celeron N, and J Series.

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Intel researchers create AI system that rates similarity of 2 pieces of code

July 29, 2020 Big Data

In partnership with researchers at MIT and the Georgia Institute of Technology, Intel scientists say they’ve developed an automated engine — Machine Inferred Code Similarity (MISIM) — that can determine when two pieces of code perform similar tasks, even when they use different structures and algorithms. MISIM ostensibly outperforms current state-of-the-art systems by up to 40 times, showing promise for applications from code recommendation to automated bug fixing.

With the rise of heterogeneous computing — i.e., systems that use more than one kind of processor — software platforms are becoming increasingly complex. Machine programming (a term coined by Intel Labs and MIT) aims to tackle this with automated, AI-driven tools. A key technology is code similarity, or systems that attempt to determine whether two code snippets show similar characteristics or achieve similar goals. Yet building accurate code similarity systems is a relatively unsolved problem.

MISIM works because of its novel context-aware semantic structure (CASS), which susses out the purpose of a given bit of source code using AI and machine learning algorithms. Once the structure of the code is integrated with CASS, algorithms assign similarity scores based on the jobs the code is designed to perform. If two pieces of code look different but perform the same function, the models rate them as similar — and vice versa.

CASS can be configured to a specific context, enabling it to capture information that describes the code at a higher level. And it can rate code without using a compiler, a program that translates human-readable source code into computer-executable machine code. This confers the usability advantage of allowing developers to execute on incomplete snippets of code, according to Intel.

Intel says it’s expanding MISIM’s feature set and moving it from the research to the demonstration phase, with the goal of creating a code recommendation engine to assist internal and external researchers programming across its architectures. The proposed system would be able to recognize the intent behind an algorithm and offer candidate codes that are semantically similar but with improved performance.

That could save employers a few headaches — not to mention helping developers themselves. According to a study published by the University of Cambridge’s Judge Business School, programmers spend 50.1% of their work time not programming and half of their programming time debugging. And the total estimated cost of debugging is $ 312 billion per year. AI-powered code suggestion and review tools like MISIM promise to cut development costs substantially while enabling coders to focus on more creative, less repetitive tasks.

“If we’re successful with machine programming, one of the end goals is to enable the global population to be able to create software,” Justin Gottschlich, Intel Labs principal scientist and director of machine programming research, told VentureBeat in a previous interview. “One of the key things you want to do is enable people to simply specify the intention of what they’re trying to express or trying to construct. Once the intention is understood, with machine programming, the machine will handle the creation of the software — the actual programming.”

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Intel Capital commits $132 million to 11 AI startups

May 12, 2020 Big Data

Intel today announced that Intel Capital, its global investment organization, committed a total of $ 132 million to 11 startups focused on AI, automation, and chipset design. It follows a year in which the firm invested $ 466 million in 36 new companies (and 35 follow-on investments) and led 72% of its deals through 22 successful exits. In 2020, Intel Capital says it’s on track to invest around the same amount — between $ 300 million and $ 500 million — in startups specializing in AI, with a particular focus on intelligent edge devices and network transformation.

Intel doubling down on AI and machine learning is business as usual. During an earnings call late last year, CEO Bob Swan said the company generated $ 3.8 billion in AI-based revenue in 2019, and that he anticipates the market opportunity will reach $ 25 billion by 2024. To position itself for growth, Intel recently acquired Habana Labs, an Israel-based developer of programmable AI and machine learning accelerators for cloud datacenters, as well as Moovit, a mobility startup that could be central to Intel subsidiary Mobileye’s plans for a robo-taxi service.

Intel Capital’s expanded investment portfolio includes Redwood City, California-based Anodot, which uses machine learning to perform autonomous business monitoring for clients across telco, finance, and digital sectors. The startup’s platform for real-time, contextual alerts helps to spot incidents — e.g., drops in success rate, customer incidents, app performance, and business metrics — that might impact revenue and costs. In fact, Anodot says it cuts incident management by as much as 80%.

Astera Labs, another new Intel Capital investment, is a fabless semiconductor company headquartered in Santa Clara, California that develops purpose-built connectivity solutions for data-centric systems. It aims to remove performance bottlenecks in compute-intensive workloads like AI and machine learning, with products that span system-aware semiconductor integrated circuits, boards and services, and more.

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Intel Capital’s investment in Hypersonix could bolster the San Jose, California-based company’s autonomous analytics platform, which targets consumer industries like retail, restaurants, hospitality, and ecommerce. Through voice and text search and data visualization, Hypersonix provides real-time actionable insights from disparate data sources like regional business performance and website traffic.

Zhejiang, China-based KFBIO, which also received an Intel Capital investment, builds pathology systems such as a scanner that ostensibly improves on traditional microscopes with digital capabilities and connectivity. Using a combination of big data, cloud computing, and AI, the company’s medical image processing tech scans and digitizes images to make them easier to share for remote consultations with experts.

New Intel Capital portfolio company Lilt provides AI-powered language translation software and services. The San Francisco, California-based firm taps machine learning, a translation management system, and professional translators to enable organizations to scale their localization programs and improve their customers’ experiences.

As for Retrace, which recently received a cash infusion from Intel Capital, it applies machine learning to real-time data to improve dental decision-making. The San Francisco startup’s predictive platform aims to reduce the oral disease burden for health plans, providers, and patients by creating a more cost-effective and evidence-based oral healthcare experience.

Other new Intel Capital investments in 2020 include:

Axonne, which is developing next-generation high-speed Ethernet network connectivity solutions for automobiles.
MemVerge, which provides petabyte-size pools of shared persistent memory and data services for AI, machine learning, and high-performance computing workloads.
ProPlus Electronics, an electronic design automation company specializing in device modeling and fast circuit simulation solutions.
Spectrum Materials, a high-purity gas and material supplier for semiconductor fabricators.
Xsight Labs, a developer of chipset designs that promise to enhance scalability, performance, and efficiency.

Intel Capital, which launched in 1991, made a total of 1,588 investments prior to today’s announcement, according to Crunchbase data. Its new commitments soberingly come as an estimated 390 startups, including companies like Uber and Airbnb, have laid off over 44,600 employees as a result of pandemic-related economic headwinds. Crunchbase anticipates a “more pronounced” reset in investments as venture firms reassess their existing funding needs.

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Intel acquires urban mobility startup Moovit for $900 million

May 4, 2020 Big Data

Intel has confirmed that it’s buying Israeli urban mobility startup Moovit, in a deal worth $ 900 million. Reports of the impending acquisition were first published by local Israeli publication Calcalist on Sunday, and in a press release today, Intel noted that it was buying Ness Ziona-based Moovit to help make Mobileye a “complete mobility provider,” which will eventually include driverless taxi services.

Chip giant Intel has a recent track record of acquiring Israeli startups. Just a few months back it paid around $ 2 billion for Habana Labs, which develops programmable AI and machine learning accelerators for datacenters. But back in 2017, Intel doled out an eye-popping $ 15.3 billion for Mobileye, a computer vision firm specializing in autonomous cars. Mobileye’s advanced driver-assistance systems (ADAS) are currently used in 60 million vehicles, and as the technology moves further toward full autonomy, Moovit’s arsenal of data will help Mobileye turn on “cost- and demand-optimized driverless” car services.

When the deal closes, Moovit will become part of the Mobileye business but will continue to operate under its own brand and run its existing partnerships. It’s also worth noting that Intel had previously invested in Moovit via its venture capital arm Intel Capital, meaning that the value of the acquisition is actually pegged at $ 840 million, net of Intel Capital equity gain.

The story so far

Founded in 2012, Moovit is best known for its consumer-facing app that’s used by more than 40 million active users globally to see the best ways to traverse a city using a combination of transport options, and even includes nifty augmented reality (AR) directions. However, the company has pivoted its core business to focus on licensing its back-end platform to third parties through a “mobility-as-a-service” (MaaS) offering. Through this, Moovit provides municipalities with data and analytics to improve city transport infrastructure, while corporations such as TomTom and Microsoft also leverage Moovit’s data to offer third-party developer access to real-time transport data to include in their own apps.

Intel acquires urban mobility startup Moovit for $900 million

Above: NYC: Moovit’s AR-powered “way finder” feature

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The value here for a company like Intel and its Mobileye subsidiary is data, which Moovit aggregates from myriad transit partners and corporations, as well as from its 40 million active users who generate more than 6 billion data points each day around traffic flow and user demand. Mobileye has made no secret of its plans for so-called “robotaxis,” and Moovit’s data will prove vital as it pushes into the driverless MaaS sphere.

Indeed, Intel and Mobileye intend to sell and lease self-driving vehicles for other companies and organizations to operate, while they also plan to deploy their own robotaxi services. But having the technology to operate fleets of driverless vehicles at scale is only part of the picture, and data and “customer-facing infrastructure” will also be required, according to Mobileye CEO Amnon Shashua.

In other words, Moovit gives Mobileye the knowledge it needs as it gears up to commercialize autonomous vehicle services in key markets around the world. Through the Moovit mobile app, Mobileye can push its robotaxi services as part of the broader trip planner offering, meaning that a commuter may see that the best way to get to their office is to take a driverless taxi from their home to the station two miles away, and then get a train the rest of the way.

The timing of Intel’s acquisition is notable, as it comes during a period of great uncertainty for companies such as Moovit — the global COVID-19 crisis has meant that public transport has been in low demand as people have stayed at home. Moovit itself publishes data regarding the impact of COVID-19 on public transit usage in key cities around the world, showing that it’s down by as much as 80% in some areas.

Above: Moovit data showing decline in public transit during COVID-19

As with other companies during the COVID-19 crisis, Moovit has sought new ways to keep business going. Last month it launched an emergency mobilization platform that makes it easier for transit organizations to redeploy their unused vehicle fleets to create new on-demand transport services for frontline workers. Corporations can also use the platform to arrange dedicated pickup services to get their essential employees safely to their place of work.

It’s not clear what role — if any — the COVID-19 crisis played in Moovit’s decision to sell now, but under the wings of a tech behemoth such as Intel, Moovit can worry just that little bit less about revenues in the coming months and years as society adjusts to what could become a “new normal” that leans heavily on remote working. The terms of the deal also seem like a decent exit for Moovit, which had raised around $ 131 million since its inception, including the $ 50 million series D cash injection led by Intel Capital in 2018.

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Intel, Mozilla, and others join pledge to make IP freely available to fight coronavirus

April 8, 2020 Big Data

A consortium of organizations including Intel, Mozilla, and Creative Commons have joined the Open COVID Pledge, an effort led by legal experts and scientists to make intellectual property (IP) available for the fight against COVID-19. The aim is to bolster cooperation in pursuit of an end to the coronavirus pandemic; companies, institutions, and universities will give free licenses to their patents, copyrights, and certain other property rights to anyone developing technologies for the diagnosis, prevention, or treatment of COVID-19.

The licenses in question are effective December 1, 2019, and they’ll last until a year after the World Health Organization declares the coronavirus pandemic to be over. Companies who make the pledge must adopt the Open COVID license, create a custom license that accomplishes the intent of the pledge, or identify existing licenses that accomplish the pledge’s goal.

According to Mark Lemley, the director of the Stanford University program in law, science, and technology, the COVID Pledge is intended to prevent researchers and entrepreneurs from being sued for tools they create during the pandemic. Once things return to normal, the hope is that companies will work together to come up with commercially reasonable license terms, but they’re able to return to owning and asserting their intellectual property if they choose.

“While we have written a model license anyone can use, many universities and companies have their own license language and terms, and that’s fine. We are encouraging them to commit to the pledge, and they can do that while implementing the pledge with their own license terms,” said Lemley in a statement.

To date, the Open COVID Pledge has received expressions of support from organizations including DLA Piper, Unified Patents, the Idea Laboratory for Intellectual Property, Fabricatorz Foundation, Universities Allied for Essential Medicines, the University of Utah S. J. Quinney College of Law, and the Program on Information Justice and Intellectual Property at American University Washington College of Law. Creative Commons says it will continue to work with these and other experts to create a framework that allows the development of diagnostic tools, treatment, and preventative solutions — and possibly even a cure or vaccine — to halt the spread of COVID-19.

“We are … giving COVID-19 scientists and researchers free access to Intel’s vast worldwide intellectual property portfolio — one of the world’s largest — in the hope and belief that making this intellectual property freely available to them will save lives,” said Intel executive vice president and general counsel Steven Rodgers in a blog post. “We will continue to invent — and protect — our intellectual property, but we offer it freely to those working to protect people from this pandemic.

Intel separately announced this morning that it would donate $ 50 million in cash and resources to anti-coronavirus efforts.

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Tag Archives: Intel

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Intel, Mozilla, and others join pledge to make IP freely available to fight coronavirus

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