Skip to content
MarketScale
‹ Back to IndustriesSoftware & Technology

Neural Codes: Transforming AI Model Building and Data Privacy

This episode of To the Edge & Beyond is Part 2 of the Edge Neural Technology series, where host Michelle Dawn Mooney is joined by Intel AI experts Zach Meicler-Garcia, Sanjana Kamath, and Sanjay Addicam to explore the groundbreaking advancements in Intel’s Edge Neural Technology. This episode delves into the inception, functionality, and far-reaching…

This story was produced through MarketScale. See how Software & Technology teams put it to work with Executive Thought Leadership.

By Michelle Dawn Mooney · AiAi AccessibilityAi AdvancementsAi in Industries
Share

Key takeaways

01

This episode of To the Edge & Beyond is Part 2 of the Edge Neural Technology series, where host Michelle Dawn Mooney is joined by Intel AI experts Zach Meicler-Garcia, Sanjana Kamath, and Sanjay Addicam to explore the groundbreaking advancements in Intel’s Edge Neural Technology.

02

This episode delves into the inception, functionality, and far-reaching…

This episode of To the Edge & Beyond is Part 2 of the Edge Neural Technology series, where host Michelle Dawn Mooney is joined by Intel AI experts Zach Meicler-Garcia, Sanjana Kamath, and Sanjay Addicam to explore the groundbreaking advancements in Intel’s Edge Neural Technology. This episode delves into the inception, functionality, and far-reaching impact of Neural Code technology, a revolutionary approach to AI model building and training that is reshaping industries like healthcare and education.

Zach Meicler-Garcia begins by tracing the origins of Neural Code technology, which draws inspiration from Dr. Sheila Nirenberg’s pioneering research at Weill Cornell Medicine. “The neural code mimics the human retina’s behavior, extracting key features from a scene and converting them into a format that AI can process efficiently,” Garcia explains. This technology reduces reliance on large datasets by focusing on motion and essential features, making it an innovative solution for AI model creation with minimal data inputs.

Sanjana Kamath discusses the practical applications and benefits of Neural Code technology, emphasizing its ability to enhance AI explainability. “The Neural Code enables the creation of shallower Convolutional Neural Networks (CNNs), which preserve privacy and remove bias, making them ideal for data-sensitive environments,” she highlights. Kamath also underscores how Intel’s no-code graphical interfaces and edge training capabilities make advanced AI accessible to users across various sectors, without the need for extensive coding expertise.

Sanjay Addicam expands on the technology’s potential, particularly in addressing challenges like hallucinations caused by generative AI video algorithms. “Even with limited data, Neural Code ensures accurate AI outputs and supports rapid model building,” Addicam explains, pointing to the future of qualitative benchmarking as a game-changer in the AI space.

Intel’s Edge Neural Technology stands as a major leap forward in AI, offering a blend of accuracy, privacy, and seamless deployment. This revolutionary approach is poised to redefine AI applications across industries, transforming how we interact with technology.

Discover more about their cutting-edge technology:

Subscribe to the “To the Edge & Beyond” podcast on Apple Podcasts and Spotify to engage with more thought leaders from the Intel and Edge Network group.

About the author

MD

Michelle Dawn Mooney is a media professional and host known for her work in broadcast journalism and B2B content.

Software & Technology: are you visible to AI?

Before they reach out, Software & Technology buyers ask AI engines which vendors to trust. See how AI describes your company today, and where competitors show up instead.

Free workspace

You just read one Software & Technology expert. Imagine publishing your whole team.

This article was produced through MarketScale. Create a free workspace and turn your own team's Software & Technology expertise into the articles, video, and social content B2B marketing buyers in your industry are searching for. No credit card, no demo required.

NPS +73 · 1,000+ creators · 38+ countries

What you get, free

Your own MarketScale Studio workspace
One video edit a month, on us
AI writing, editing, and publishing tools
In-platform coaching to learn the system

More Software & Technology Insights

The 2026 Forbes AI 50 reveals a $305.6 billion private market consolidating fast around a handful of giants

The 2026 Forbes AI 50 reveals a $305.6 billion private market consolidating fast around a handful of giants

The Forbes AI 50 list in 2026 highlights a $305.6 billion private AI market that is rapidly being dominated by a few major companies. OpenAI and Anthropic together account for 80% of the total funding among the listed companies, indicating a significant capital concentration. However, the emergence of 20 newcomers suggests that there remains room for innovation and growth, especially in sectors like fintech.

  • 01OpenAI and Anthropic account for 80% of the total funding on the Forbes AI 50.
  • 02The total market size for the AI industry is valued at $305.6 billion.
  • 03There are 20 new companies on the Forbes AI 50 list, indicating continued innovation.

Aug 1, 2026

Employee distrust and skills gaps are the real barriers slowing enterprise AI scale in 2026

Employee distrust and skills gaps are the real barriers slowing enterprise AI scale in 2026

The main challenges to scaling enterprise AI in 2026 are employee distrust and a widening skills gap rather than technological readiness. Companies like Microsoft, Salesforce, and Google have the platforms ready, but workforce trust and skills remain barriers.

  • 01Employee distrust is a significant barrier to scaling enterprise AI.
  • 02A widening AI skills gap is hindering technological progress within companies.
  • 03Platforms from major companies like Microsoft, Salesforce, and Google are technically ready for AI scaling.

Aug 1, 2026

Anthropic and Blackstone launch $1.5B AI implementation firm Ode, betting enterprise deployment beats model-building

Anthropic and Blackstone launch $1.5B AI implementation firm Ode, betting enterprise deployment beats model-building

Ode, a $1.5 billion joint venture involving Anthropic, Blackstone, and Goldman Sachs, aims to integrate AI into enterprise operations. The venture employs 100 engineers to focus on the deployment of AI technology across various business sectors. The firm's strategy is to prioritize AI implementation over developing new AI models.

  • 01Ode is a $1.5 billion joint venture promoting AI integration in enterprises.
  • 02The venture employs 100 engineers for AI deployment.
  • 03Ode focuses on implementation rather than creating new AI models.

Jul 31, 2026

Explore More Software & Technology Insights

Read more expert perspectives from across Software & Technology.

Browse Software & Technology Hub

About the Expert

MD
Michelle Dawn Mooney

Michelle Dawn Mooney is a media professional and host known for her work in broadcast journalism and B2B content.

For B2B teams

Your experts could be publishing here

Stories like this one run on content MarketScale captures from real practitioners. See how your team's expertise becomes coverage in Software & Technology and beyond.

Book a 15-minute demo

Or call us. No forms required. We pick up. 214-945-2512