Intel on AI

In this Intel on AI podcast episode: Safety and productivity issues are crucial for engineering, manufacturing, and industrial organizations. Ensuring that workers are in their safe and respective area not only helps prevent injuries but also increases productivity and compliance for a company. Apoorva Ankad, Head of Computer Vision and AI Group at Deevia Software, joins the Intel on AI podcast to...

In this Intel on AI podcast episode: Industrial operations such as metal manufacturing need to keep track of how well their facilities, time, and materials are being utilized in order to be as productive and profitable as possible. Yet, there can be 100s of sensors in a manufacturing plant and capturing, analyzing, and making predictions based on all that data can be very difficult. Also, ensuring...

In this Intel on AI podcast episode: The COVID-19 coronavirus, since its initial outbreak, has quickly become a global pandemic and the inadequate amount of lab tests available for people suspected of infection have posed serious risks to public health and efforts in containing the virus. Jingwen Jia (Wendy), the Assistant General Manager at Huiying Medical (HYHY), joins the Intel on AI podcast to...

In this Intel on AI podcast episode: Retail shoppers around the world are always looking to have a more personalized, convenient, and overall better shopping experience when they visit stores. With the advent of advanced cameras, sensors, and AI technology, smart stores are eliminating the need for customers to wait in line, scan their purchases, or even complete a payment transaction with a cashi...

In this Intel on AI podcast episode: As wind turbines proliferate and grow in size and complexity, the biggest challenge to Wind Energy is the high cost of Operations and Maintenance. Manual inspection and maintenance is dangerous and expensive. With the advent of drones, gathering maintenance footage has become much easier, but without the use of AI technology, inspecting tons of footage and data...

In this Intel on AI podcast episode: 4G/ LTE network is a preferred method of information transfer today and is becoming more and more crucial in our extremely connected lives. To keep up with the ever-increasing volume of traffic, the network is constantly changing and becoming more and more complex. Legacy rules-based network automation techniques are not working, and communication service provi...

In this Intel on AI podcast episode: Sparse modeling methods can improve the interpretability of predictive AI models and is widely used in academia today. Yet despite advances in the field, issues remain when sparse modeling meets real-life applications. Adrian Sossna, the Chief Marketing Officer at HACARUS, joins the Intel on AI podcast to talk about how the SPECTRO visual software inspection mo...

In this Intel on AI podcast episode: In industrial and manufacturing settings plant safety issues like oil spills, chemical spills, and PPE (personal protective equipment) violations can happen often. These issues put lives at risk, the environment in danger, and bring down productivity and profitability of the organization. Yet, addressing these issues automatically with AI is a challenging poten...

In this Intel on AI podcast episode: Enterprises are in a race to become more agile, nimble, and responsive to remain competitive in today's fast-changing marketplace. Turning to machine learning (ML) and data science is essential. Today companies can spend millions building their own internal ML pipelines that need ongoing support and maintenance. There are numerous tools that exist for developin...

In this Intel on AI podcast episode: To remain competitive businesses need to utilize their data to the fullest and make data-driven decisions at all levels. Yet, collecting and analyzing data can be expensive when hiring external expertise or time consuming when training internal teams. Vivek Mishra, Head of Technology at vPhrase Analytics, joins the Intel on AI podcast to talk about their AI-bas...

In this Intel on AI podcast episode: Every customer call is an opportunity to gain information about customer preferences and provide a positive experience for callers. Yet, call centers can be expensive to run and maintain, especially in the current environment where many workers are unable to travel to their job due to local and state govt restrictions. Filling the call center agent role with an...

In this Intel on AI podcast episode: The Internet of Things (IoT) is producing a tremendous amount of data. But companies need to make sense of the data and AI is a clear answer to analyze and act on that data to deliver the full potential of IoT. Previously, combining AI and IoT was relatively unthinkable. Now it is an incredibly fast growing trend, often referred to as AIoT. Bill Roberts, Senior...

In this Intel on AI podcast episode: Healthcare workloads, particularly in medical imaging, require more memory usage than other AI workloads because they often use higher resolution 3D images. Deep learning (DL) models developed from these data sets require both high accuracy and high confidence levels to be useful in clinical practice, but this is incredibly data and compute intensive. David Oji...

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 can be even more challenging and limit many business from being able to take advantage of advanced technologies like machine learning (ML)....

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 studies and advertising testing. Millions are spent on creating promotional materials that have little to no analytics behind them. The ability to analyze...

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 money to address. Antonio Filho, Head of Machine Learning at Nuveo, joins the Intel on AI podcast to discuss how the Nuveo Ultra OCR (Optical Character...

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 of the curve in such a fast-paced industry. Previously, trying to analyze market data to predict a model's success could take weeks. Fréd...

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 especially costly with legacy equipment that is not enabled with the necessary sensors, intelligence, or ability to communicate with...

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 and approved by your insurance company. This process is costly and complicated for both the insurance company and consumers and can be a pain point for all parties involved. Vladimir Starostenkov...

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 attacks with embedded images and video manipulation which evade traditional detection methods and are very difficult for u...

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 other information to determine the type of infection so that proper medication can be suggested for a cure. This process can be challenging for providers...

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 deepfakes can present to elections, banking, security, and many other sectors. A deepfake is the use of AI or machine learning techniques to take an existing image or vide...

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 between Intel and Supermicro. He explains how, in addition to hardware, Supermicro is providing many solutions to their customers including their Resource Savings a...

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 MRI scanner and adding unnecessary steps to set up each scan. It can also introduce inconsistencies into images taken over time if parameters or positioning are slight...

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 AI technologies to drive a wide array of innovative solutions. Deepak discusses how the Wipro Pipe Sleuth solution uses artificial intelligence (AI) to automatica...