The Alldus Podcast: Our Top 5 Computer Vision podcasts

Blog | July 13 2023 | Alldus Recruitment

In an era defined by fast-paced technological advancements and the ever-increasing availability of visual data, Computer Vision has emerged as a powerful tool with great potential. From analyzing images and videos to extracting meaningful insights, Computer Vision is revolutionizing many industries, enhancing automation and transforming the way we perceive and interact with the world.

We’ve had the privilege of interviewing over 600 guests in the past five years for The Alldus Podcast, including renowned leaders and innovative companies at the forefront of harnessing the power of Computer Vision. Our discussions have spanned a wide range of topics and industries, shedding light on the transformative impact of Computer Vision in fields such as autonomous vehicles, robotics, healthcare and surveillance to name a few.

So, without further ado, we present a selection of our favorite episodes that delve deep into the exciting world of Computer Vision.

1. AI in Action E441: Shahmeer Mirza, Director of R&D and IT Strategy at 7-Eleven

Back in May 2023, Shahmeer Mirza, Director of R&D at 7-Eleven spoke about how his team focuses on customer-facing innovation using machine learning and computer vision. They work on building novel products, such as frictionless retail and IoT infrastructure, collaborating with the data science team for analysis and forecasting. Shahmeer shared how he is excited about scaling their computer vision capability for self-checkout, where customers can use real-time computer vision to interact with the system. They are also focusing on collecting customer interaction data to enhance object and product recognition.

In the episode, Shahmeer describes: “What I’m probably most excited about is starting to see a lot of the investments we’ve made in building baseline computer vision and machine learning capability reaching customers. We ran a pilot very successfully last year for several months where we had this core computer vision capability running for our customers to be able interact with our self checkout system. So they would place these items on a kiosk. They would get all of the items recognized in real time, and they’d be able to check out because the cart would be generated instantaneously. This was very successful and so one of our efforts this year is really focusing on scaling that capability out.”

Check out Shahmeer’s full podcast at this link

2. AI in Action E286: Dennis Wall, Founder at Cognoa

Dennis Wall, Founder at Cognoa featured on the show in November 2021 as he discussed their mission is to accelerate the diagnosis of autism, so that children can receive early intervention therapy. By analyzing short video clips, Cognoa’s AI technology can detect key features indicative of autism, reducing the complexity of diagnosis and enabling early intervention. Dennis explains how they have made significant advancements in computer vision and machine learning, allowing for the automatic detection of important features in video data. The company is also developing tools like the Superpower Glass program, which uses augmented reality to deliver therapy to children with autism.

In the episode, Dennis discusses: “So we built a computer vision tool kit that would really work within the natural homes. I mean with all the lighting variation and head tilt, pose variations and all of those sorts of things, shadows so that it would be robust in real time. It works by interfacing with the Google glass system. We leverage the outward facing camera, which watches the world around the around the child, who’s wearing the glasses, captures images of individuals with whom the child is interacting and with our computer vision toolkit, we can process those faces. We can identify that they’re our faces and then we process what those faces are emoting and provide those emotional cues back to the child.”

Check out the full podcast with Dennis at this link.

3. AI in Action E312: Carlos Anchia, Co-Founder and CEO at Plainsight

In March 2022, Carlos Anchia, Co-Founder and Chief Executive Officer at Plainsight spoke about how they streamline Vision AI for enterprises with new ways to analyze, share and benefit from valuable visual information. Carlos discussed how their platform enables businesses to build computer vision solutions as he describes the process of training computer vision models, and the importance of adoption and ROI for businesses. He discusses the company’s opportunities in the field of computer vision, predicting that computer vision will have a significant impact in various industries, particularly with the advancements in edge technology.

In the episode, Carlos tells us: “We’re now going to enable a variety of different use cases to where computer vision, when pushed down into these edge locations, can actually really produce a savings and cost and value into the solution itself. We have a new way of doing what’s considered a legacy process in the past. Now it’s completely electronic because we were able to implement a technology to solve that. I see computer vision being that same technology that enables a variety of different cases for images and video as we go to progress into this technological space where the models are more accurate than they were five years ago. The edge infrastructure is more powerful, more cost effective than it ever was.”

Check out the full podcast with Carlos at this link.

4.AI in Action E404: Tigran Petrosyan, Co-Founder and CEO at SuperAnnotate

In December 2022, Tigran Petrosyan, Co-Founder and CEO at SuperAnnotate discussed how SuperAnnotate provides a labeling infrastructure for machine learning applications, enabling companies to label various types of data, such as images and textual data to train their AI models. They are helping companies build the next generation of computer vision products, including working with a wide range of industries, including autonomous vehicles, aerial imagery analytics and content moderation. Tigran also shares their upcoming plans, including a data annotation tool for data scientists and the integration of new data types into their infrastructure, such as LIDAR and 3D point cloud solutions.

During the podcast, Tigran highlights: “Nowadays with machine learning and computer vision, one can actually see what’s in the image. For example, for autonomous vehicles, if you want to build like a self-driving car, your camera can recognize where are the other people street lines, the trees, other cars, et cetera. So in order for that to work, people label images in similar situations, let’s say in the image, you kind of point out where are the cars? Where are the trees, et cetera. We’re building that labeling infrastructure for various type of data, like images, videos, any kind of textual data NLP to help this machine learning applications to build their products.”

Check out the full episode with Tigran at this link

5. AI in Action E447: Justin Nguyen, Head of Customer Service Data Engineering and Analytics at Chewy

Back in May 2023, Justin Nguyen, Head of Customer Service Data Engineering and Analytics at Chewy shared stories about his personal projects, such as using computer vision to monitor his baby daughter’s well-being and creating an algorithm to generate unique names for his wife’s garden. He also discusses an early computer vision project that involved object recognition to detect items in his refrigerator and generate a grocery list. Justin further discusses the integration of AI into everyday life and the importance of using AI to save time and streamline tasks. He also emphasizes the need to incorporate data proactively in decision-making processes and the excitement he feels about the future of AI and data-driven strategies.

In his discussion during the episode, Justin told us: “One of the first things which I’m sure many people can relate to is I searched the baby market to find the best products, including baby monitoring products. Eventually I came to the con conclusion that I would build my own. So what I did was I installed an IP camera above her crib, it was pointed down looking at her and just basically making sure that the color of her cheeks were within the right range and then it could also figure out whether or not she was awake or sleeping by using object recognition to find her eyes and then see if they were open or closed.”

Check out Justin’s full podcast at this link

If you’re interested in exploring our latest jobs within Computer Vision and Machine Learning, check out our live vacancies or upload your resume today to keep up to date with all the latest opportunities.

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