10 things our new tech podcast on iTunes can teach you

Orange Silicon Valley
7 min readNov 1, 2018


Image credit: Orange/Orange Silicon Valley

By Colette Wright

New technologies can bring people together, enable them to do better work, and help them to live better lives at home. In the Orange Silicon Valley Bistrocast, our recently launched podcast about emerging tech and the work our experts are doing with it, we set out to explore what’s happening now and what lies ahead.

Since the podcast debuted three episodes ago, the Bistrocast has already featured Mike Vladimer discussing the future of the Internet of Things, Will Barkis assessing the goals of Smart Cities projects, and Sarah Luger mapping out the intersection of artificial intelligence and natural language processing. Now, all of those episodes and more can be found when you listen and subscribe to the Bistrocast on iTunes, Google Play, or Spotify.

Here are 10 of the most interesting topics that you’ll find in the first episodes:

Mike Vladimer (Image credit: Orange Silicon Valley)

1. The core ingredients for an IoT product

“IoT is comprised of four things: sensors, connectivity, computation, and user interface. It used to be too expensive to build IoT products, but the core components have dropped so much in price that IoT systems have proliferated,” explained Mike Vladimer, the co-founder of Orange Silicon Valley’s IoT Studio, in the Bistrocast’s first installment.

Twenty years ago, products with similar features cost millions of dollars to create. Now, it is more technologically feasible and economically affordable to implement these four pieces of tech in an IoT product. Sensors gather data, connectivity sends it to the Internet, computation extracts some meaning and insight from the collected data, and user interface exposes this information to the consumer.

2. How to differentiate and categorize IoT products

Mike has a framework he calls IoT 1.0 and 2.0: “With IoT 1.0, many companies took the approach ‘if we can IoTify it, let’s IoTify it.’ Although those products do create some value for some people, it’s not game changing. Instead, I’m interested in finding markets where people are in intense pain and solving their problems,’” Mike told the podcast. “That to me is IoT 2.0. IoT 2.0 is ‘Let’s be creative, let’s be imaginative, let’s not just IoT-ify solutions to existing problems, let’s solve problems we could never solve before.’ ”

Mike argues that all IoT devices need to start with a problem. He believes that just because an IoT product can be created, that does not mean that it should be created; after all, not everything is considered useful to consumers. A successful IoT product excel at fixing a niche problem and of course must me much better than the current solution. However, if a current solution is good enough, then there is no problem that IoT can meaningfully solve.

“Data is all about understanding what’s happening. Now we can optimize solutions with all the data we’re collecting.”

— Mike Vladimer

3. Why data will become an essential part of the future

“People say data is the new oil. What was the meaning of fossil fuels for humanity?” Mike posed to us in the first episode. “I argue that it was an unlimited access to power. Before fossil fuels, if you needed lots of power to do something — lift heavy objects, travel far distances — you just couldn’t do it. Then suddenly with fossil fuels, you suddenly could. Similarly, data is unleashing a wave of understanding what’s happening. Now we can optimize solutions with all the data we’re collecting.”

In this reference, data implies unleashed optimization, as oil unleashed a source of power that changed the world. Oil and fossil fuels lifted physical constraints, and in doing so have made things cheaper and more attainable while making tasks more realistic and doable. Having ready access to large amounts of data can be impactful and people are still trying to find the most valuable ways to put that data to use.

Will Barkis (Image credit: Orange Silicon Valley)

4. What defines a smart city

“What is needed for a smart city is based on the local problem space,” said Will Barkis, the principal for Orange Silicon Valley’s Smart Cities formation, in the second episode of the Bistrocast. “There’s an element of human-centric design, and a user-centric focus. That is a universal thing as far as the outwardly facing Smart Cities applications are concerned.”

The population of cities will double by 2050, according to United Nations estimates, and it is important to understand how to accommodate that population growth. By focusing on sustainability goals, cities can take meaningful steps to improve the quality of life for their residents and visitors. Three essential pieces of Smart Cities solutions to some of those problems include data, connectivity, and collaboration, according to Will.

5. The goals for Smart Cities technology

“At the core, you could argue [Smart Cities technologies] are about modernizing and digitizing government services,” Will stated. “I think it’s useful to expand the circle beyond that….” Specifically, Will pointed to ridesharing services and last-mile solutions such as scooters that are helping urbanites to complete their daily commute puzzles.

On the national level, Smart Cities projects need to focus on people and redefine citizen engagement, according to Will. It is essential that governments understand how to respond to technologies in ways that are beneficial to rapidly growing populations. Concerns arise with connecting more people and businesses across a wider space, and technology has the potential to address some of these challenges. Some of the consequences of rapidly expanding urban populations include environmental, economic, and social equity concerns, which are areas where Smart Cities tech can have an impact.

6. Examples of Smart Cities innovation

“We’re seeing things like street lights being deployed,” Will said, discussing Smart Cities projects that he is currently watching. “San Diego is doing a project on LED lights. The reason to put them in is because of energy efficiency; we aren’t putting as many lightbulbs in.”

Larger cities like San Diego, San Francisco, and New York are already taking steps to become “smarter.” This is easier to do in these places as opposed to smaller more rural areas because they have business models that can support them and build future infrastructure.

Sarah Luger (Image credit: Orange Silicon Valley)

7. How natural language processing is used

“Natural language processing (NLP) is an attempt to understand spoken or written language by a machine that speaks a different language,” said Sarah Luger, a research scientist at Orange Silicon Valley, in the Bistrocast’s third episode. “This domain in some degree is called human-computer interaction.”

NLP is a subdomain of AI that focuses on machine language and text translation. Common use cases for NLP include text summarization, machine translation, named entity recognition, semantic role labeling, and anaphora resolution.

8. How artificial intelligence and machine learning are related

Artificial intelligence is an approximation of human intelligence and uses past human decisions and data to make future predictive decisions,” Sarah explained. “Machine learning is a set of mathematical algorithms for using those predictions and understanding patterns.”

Machine learning is used in math and statistics, and is not purely an NLP or AI technique. Both provide skills and tools that are useful in all domains. The machine learning approach to how we record data, what are your decisions and what those are moving forward, have the basis to be in many different domains.

“The Holy Grail right now is domain expertise plus AI.”

—Sarah Luger

9. How artificial intelligence can be used across professions

“The Holy Grail right now is domain expertise plus AI,” said Sarah. “AI has been very popular in domains that have already been super technical.”

This trend can be seen in action as universities encourage more interdisciplinary research. These collaborations offer a broader dissemination of tools and skills that could be useful to people across many domains.

10. Human-computer interaction

“Humans have intentionality when we speak to each other,” Sarah told the podcast. “We are on the same page, we want to be here. Computers and aids like Alexa do not. We’re just giving commands and getting information back; it’s hard to chain that into a conversation.”

Human-computer interactions are likely to undergo ongoing changes far into the future and have been around since computers first appeared. Now, people are transitioning from using a mouse and touchpad to communicating with voice and gesture in many cases. However, the way humans engage with computers is not completely natural. We do not talk to computers like we talk to our friends, the conversations can be silted and unnatural. But this is an opportunity to improve and optimize technology that is still in its early stages of mass adoption. And that is precisely the space we intend to explore more deeply with these and other technologies in future episodes of the Orange Silicon Valley Bistrocast.

Find and subscribe to the Bistrocast on the following platforms:

iTunes | Google Play | Spotify

Disclaimer: The views and opinions expressed in this article belong to the author and do not necessarily reflect the position or views of Orange or Orange Silicon Valley.



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