Intel, Georgia Tech, and MIT code similarity project could address tech shortages


The machine inferred code similarity system has recorded scores that are at times 40 times more accurate than other existing systems, according to Intel.


Image: Intel

In the era of digital transformation, more companies are looking to leverage automation to streamline their business models and enhance efficiencies. At the same time, many companies are struggling to onboard the talent to fulfill their operational objectives. The tech talent shortage has been widely discussed over the past few years.

In 2017, it was estimated that there would be as many as 1 million developer positions left unfilled by 2020, according to

. At the time, more than 80% of representatives on the TechRepublic CIO Jury reported difficulties finding necessary tech talent at their organizations. The coronavirus pandemic has even highlighted the risks associated with scant programmer talent; namely COBOL programmers to assist with older mainframe systems.

SEE: Quick Glossary: DevOps (TechRepublic Premium)

To assist, a consortium of organizations including Intel are working to develop a system to determine functionality similarities between snippets of code.

On Wednesday, Intel released details surrounding the programming project in partnership with Massachusetts Institute of Technology (MIT) and Georgia Tech (Georgia Institute of Technology). The machine inferred code similarity (MISIM) system has been engineered to study the overall structure of code as well as analyze the “syntactic differences of other code with similar behavior” to in essence “learn” the code’s intent.

In general, machine programming (MP) efforts are focused on enhancing development production via automated tools, according to Intel. The company believes that code similarity is crucial to a host of MP tools.

“Intel’s ultimate goal for machine programming is to democratize the creation of software. When fully realized, MP will enable everyone to create software by expressing their intention in whatever fashion that’s best for them, whether that’s code, natural language, or something else. That’s an audacious goal, and while there’s much more work to be done, MISIM is a solid step toward it,” said Justin Gottschlich, principal scientist and director of Intel’s machine programming research, in a press release.

SEE: Top 5 programming languages for systems admins to learn (free PDF) (TechRepublic)

Today, there are a number of challenges surrounding building these code similarity systems, as accuracy exists as a “relatively unsolved problem,” per Intel. Such a system aims to understand if two snippets of code express analogous qualities or seek comparable outcomes. This is “a daunting task when having only source code to learn from,” as Intel points out.

When analyzing a pair of code snippets, MISIM is able to accurately calculate computational similarities, per Intel. MISIM’s context-aware semantic structure (CASS) is the differentiating factor between this code-similarity system and others. Instead of trying to discern how a snippet of code does something, MISIM’s CASS allows the system to more aptly discern what this code is intended to do.

Within the structure, neural networks assign “similarity scores to pieces of code based on the jobs they are designed to carry out.” MISIM identified “similar pieces of code up to 40x more accurately than prior state-of-the-art systems,” according to Intel.

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Intel spends $30 million to help students and cities cope with the coronavirus


The Pandemic Response Technology Initiative also is providing financial and technical support to help find treatments and a vaccine.

Image: Intel

Intel and partners have spent $30 million reimagining education, healthcare, and COVID-19 testing as part of the company’s Pandemic Response Technology Initiative. Intel launched the $50 million initiative in April to use technology to help with the diagnosis of the coronavirus, support disrupted educators and students, and fund innovative new ideas and projects.

Rick Echevarria, vice president in the Sales, Marketing and Communications Group, leads the Initiative. He said that early on Intel focused on providing networking, compute, and storage services to healthcare facilities that needed infrastructure to scale telemedicine services.

Intel also provided the back end infrastructure for virtual intensive care units. With a virtual ICU, doctors can monitor patients remotely by gathering and analyzing data while minimizing contact between nurses and patients.

“This allows hospitals to scale services while at the same time enabling and protecting the health of the frontline workers,” he said.

Intel’s contributions to these health, education, and research projects have been a mix of tech support and funding. The company has donated cloud services donated in each project category to provide connectivity and content.  

“The infrastructure element is front and center in most of the solutions we’re working on,” he said.

SEE: Return to work: What the new normal will look like post-pandemic (free PDF) (TechRepublic)

In one of the long-term projects, researchers looking for a vaccine for the virus have asked for help with compute cycles, for example.

Now that these immediate needs are met, the initiative’s focus is more long-term issues, such as providing technology and educational content for students who might otherwise be left behind during all-online schooling, aiding businesses as they reopen, and using Intel’s tech and money to search for diagnoses, treatments and vaccines.

There are three components to the education efforts: devices, content, and backend services. 

“We have facilitated the delivery of devices to students, but devices alone don’t solve the problem,” Echevarria said. 

Echevarria said that Intel’s IoT products and services including edge computing analytics will play a big role in projects focused on helping companies reopen offices. 

Two other efforts that will support reopening are focused on air and water quality. Water Lens, a startup in the Ion Smart and Resilient Cities Accelerator, offers genetic water testing technology. The company is conducting a pilot program with Houston to test for COVID-19 in wastewater, which could help determine the community’s true infection rate. Intel and the city launched the accelerator in 2019. Echevarria also said that other projects in Innovation cohort of the Initiative are focused on air quality and how to ensure safe social distancing at work.

Intel identified these lessons learned from the pandemic response initiative:

  1. Technology is more important than ever: Intel and its customers have broken down silos to move more quickly than ever; “We’ve thought creatively and pulled together customers to provide services that are saving lives, educating students and keeping our community infrastructure solid.”

  2. Data collaboration and sharing is vital: The whole world has become a peer community. With the help of federated learning, researchers can privately share patient data as they collaborate to create a vaccine or treatment program. They can access a rich world of data to make better decisions and follow groundbreaking clues, all without breaching privacy laws.

  3. Better health powers economic recovery: People’s health will be critical to the world’s economic recovery, just as the economic recovery will be key to everyone’s health. Going back to doing things the way we did them before won’t carry over after the coronavirus is solved.

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