In this Intel on AI podcast episode: Today, the deluge of data has made demand for machine learning engineers explode. Also because distributed computing is a challenging and elite subfield of computer programming, finding engineers to address these skill sets [See the full post…]

In this Intel on AI podcast episode: Knowing how a product or service makes a customer feel enables companies to make successful products that their customers enjoy. Yet measuring this traditionally takes a lot of time and effort through impact [See the full post…]

In this Intel on AI podcast episode: Manually gathering, processing, and analyzing unstructured data is extremely effort and time intensive. For industries such as insurance or finance this is a big issue and can cost an organization much time and [See the full post…]

In this Intel on AI podcast episode: Gauging prospects and predicting the direction of the fashion industry is incredibly difficult. Businesses and investors hypothesizing the success of rising stars in the industry have to make real-time decisions to stay ahead [See the full post…]

In this Intel on AI podcast episode: Before an MRI technologist can scan a patient, they manually specify the slices they want the MRI to acquire. This can take several minutes of tweaking, leaving a patient waiting anxiously in the [See the full post…]

In this Intel on AI podcast episode: One of the biggest challenges manufacturing operations face when adopting digitalization and intelligence is the cost and complexity to instrument existing machines, connect them to a network, and deploy relevant software. This is [See the full post…]

In this Intel on AI podcast episode: When making car insurance claims it can take a lot of time to have a claims adjuster inspect the damage to your car and then get the estimate from a body shop reviewed [See the full post…]

In this Intel on AI podcast episode: Today, social media is among the primary business and communication platforms for modern organizations, yet, social media networks are incredibly large platforms with some of the most complex security challenges. Increasingly attackers hide [See the full post…]

In this Intel on AI podcast episode: The process of diagnosing a patient with chest abnormality is done by radiologists and doctors with a lot of experience and expertise. This involves looking for the presence of foreign bodies, infiltrates, and [See the full post…]

In this Intel on AI podcast episode: Recording live at the Intel AI Summit event in San Francisco California, Ben Taylor the Chief Data Officer of Zeff, joins the Intel on AI Podcast to discuss deepfake technology and risks that [See the full post…]

In this Intel on AI podcast episode: Recording live at the Intel AI Summit event in San Francisco California, Ray Pang Head of Technology Enablement at Supermicro, joins the Intel on AI Podcast to talk about the long term collaboration [See the full post…]

MulticoreWare’s LipSync technology uses Deep Neural Networks to “watch” and “listen” to videos and determine if content is correctly synchronized. Trained classifiers are used to find and match human faces to human speech, allowing LipSync to detect errors that are [See the full post…]

In this Intel on AI podcast episode: Recording live at the Intel AI Summit in San Francisco California, Deepak Dinkar Senior Practice Manager at Wipro Technologies, joins the Intel on AI Podcast to discuss how Wipro is working with Intel [See the full post…]

In this Intel Chip Chat audio podcast with Allyson Klein: Academic research and theoretical work on deep learning have predicted an exciting future for deep learning, and now real-world technology is catching up with some of the most exciting potential [See the full post…]

In this Intel Chip Chat audio podcast with Allyson Klein: Deep learning workloads have evolved considerably over the last few years. Today’s models are larger, deeper, and more complex than neural networks from even a few years ago, with an [See the full post…]

In this Intel on AI podcast episode: Enterprises today have exploding volumes of data which is growing the scale and complexity of data centers and often result in unplanned IT downtime. This disrupts mission-critical operations, causes loss of data, and [See the full post…]

In this Intel on AI podcast episode: Creating, maintaining and deploying data models that allow businesses to gain actionable insights can require a lot of time and effort due to the vast amount of data to process. Also, machine learning [See the full post…]

In this Intel on AI podcast episode: Counting and identifying characteristics of crowds can provide organizations with a lot of valuable insights. Yet challenges like image distortion, density, and different camera angles can make analyzing images accurately very challenging. Ganes [See the full post…]

In this Intel Chip Chat audio podcast with Allyson Klein: Natural Language Processing is a complex and important field of AI. It’s what allows AI assistants to understand human voices, chatbots to understand typed text, and AI to read scanned [See the full post…]

In this Intel on AI podcast episode: Accurately answering clinical and billing questions by reading patient records, which can be hundreds of pages long, is a challenge even for human experts. While traditional rule-based or expression-matching techniques work for simple [See the full post…]

In this Intel on AI podcast episode: Enterprises today are attempting to use Artificial Intelligence (AI) to tackle more and more complex challenges. Yet, many of the AI applications today are unable to cope with optimization and automation challenges in [See the full post…]

In this Intel on AI podcast episode: Colorectal cancer is the one of the most common cancers worldwide, and in about half of patients it can spread to the liver and lead to greater complications. Traditional manual examinations of tumors [See the full post…]

In this Intel on AI podcast episode: There is a massive amount of insight to be gained by studying brick and mortar customer behavior. Yet capturing, labeling, and analyzing that data can be a very complicated and compute intensive activity. [See the full post…]

In this Intel on AI podcast episode: There are many individuals (makers) creating artificial intelligence (AI) enabled solutions and many of which may help drive AI to the next level. Yet, there is a challenge for makers when moving from [See the full post…]

In this Intel on AI podcast episode: As artificial intelligence (AI) technologies rapidly advance many companies would like to take advantage of the potential of AI but can’t because they do not have the resources or skills for modeling and [See the full post…]