Data Futurology - Leadership And Strategy in Artificial Intelligence, Machine Learning, Data Science

This week, we are joined by Ivan Liu. Director of Engineering at Rokt. He specialised in software engineering, machine learning and cloud architecture. Tune in for the full conversation where Ivan talks about ML ops and ML Engineering. Enjoy the show! Thanks to our sponsor Talent Insights Group! Read the full podcast episode summary here. --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

In this week’s podcast episode, Felipe spoke with Chris Dowsett, Head of Decision Science and Analytics at Spaceship. Chris has been working in Data Science, Analytics and Decision Science for the past 18 years. His specialty is helping business leaders make decisions and solve business challenges using data science and analytics. Don’t miss this episode as Chris talks about the difference between data and decision science, plus much more! Enjoy the episode. Thanks to our sponsor Talent Insights Group! Read the full podcast episode summary here. --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

For the first time in Data Futurology podcast, we’ll be having a two-in-one episode. In the first part of this episode, Felipe Flores is interviewed by AI today podcast hosts Kathleen Walch and Ron Schmelzer. Cognilytica's AI Today podcast focuses on relevant information about what's going on today in the world of artificial intelligence. In the latter part of this episode, Felipe interviews Kathleen and Ron to talk about certain challenges and finding out the real potential of AI. Enjoy the show! Thanks to our sponsor Talent Insights Group! Read podcast full episode summary here. --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

In this week’s episode, we are joined by Maggie Shi, Head of Solutions Engineering Facebook ANZ, Japan and Korea. Maggie combines her 20+ years of software development, technical directing and project management experience into her current role at Facebook. She has a strong background in Java/C++ development which she has used as a foundation to lead strong technical teams. Tune in for the full conversation where Maggie deep dives into privacy-preserving and data sharing. Enjoy the show! Thanks to our sponsor Talent Insights Group! Join us at upcoming events https://www.datafuturology.com/events Read full episode summary here. --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

We are joined by Florian Douetteau, a legend in the industry, who built a unicorn company within the data space. He is the CEO of Dataiku, a platform that assists in systemising the use of your data for exceptional business results. Florian is a mathematician by trade, however he found the mathematics world too theoretical for his liking and wanted to move into a space where he could work on practical applications of the discipline. He realized one of the things avoiding the widespread use of business intelligence was the fact that whatever the advance in the reporting, data itself was a problem, and in his own words, when you’ve got a problem and you want to solve it at scale, software is a good solution. That’s where Dataiku comes in, through their platform they enable teams to create and deliver data and advanced analytics using the latest techniques at scale. Their motto is “Leave no one behind with AI.”, which Florian explains comes from the fact that for a data & AI project to have the right impact, you need a balance in terms of who is behind the wheel. It shouldn’t be just data scientists, you also need business stakeholders to participate. Ultimately, Dataiku is all about making data science and AI accessible to all the people in the organisation and enable them to take part in building AI and consuming AI-driven applications. Tune in to hear more about Florian’s start in the data space, the lessons he has learned along the way and how he is working towards the democratisation of data through his company, Dataiku. Enjoy the show! Thanks to our sponsor Talent Insights Group! Read full episode summary here. --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

In this episode, we speak with Chris Wexler — CEO of Krunam. Krunam is in the business of removing digital toxic waste from the internet using AI to identify CSAM and other indicative content to improve and speed content moderation.  Krunam’s technology is already in use by law enforcement and is now moving into the private sector. In this sensitive and equally essential topic, we’ll learn from Chris why AI is the future of fighting child sexual abuse material. Read Full Episode Summary here. Thanks to our sponsor Talent Insights Group! Join us at upcoming events https://www.datafuturology.com/events --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

In part 2 of our interview with Steve Nouri, he spoke about AI specializations and share his thoughts about AI innovation in developing countries. He says that AI is quickly evolving and we’re going to see a lot of specialized people working in the AI field in bigger organizations. Also in this episode, we discuss personal branding and its importance for a Data Scientist. Steve shares first-hand experience on how he got started with his personal branding years ago and how it helped him with his role at the Australian Computer Society. Don’t miss this episode as Steve shares his wealth of information with us. Enjoy the show! Read Full Episode Summary here. Thanks to our sponsor Talent Insights Group! --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

We are joined by Steve Nouri, Head of Data Science & AI at Australian Computer Society and member of Forbes Technology Council. With 450k+ followers on LinkedIn,  Felipe calls him  “LinkedIn’s King of AI”. Steve’s background is in software engineering but he got interested in data over 14 years ago. He went on to get a masters degree in Data Analytics and then transitioned into the data field completely. In his role as Head of Data Science & AI at ACS, he encourages and helps people interested in the data world to pursue a job in the field. He is passionate about giving back to the community and he explains where his passion for data science comes from. Steve knows the potential AI has to create a huge impact in society, whether it be positive or negative. That’s why he dedicates so much of his time to work towards the ethical use of AI and to advance the applications of this technology for the greater good. Tune in to learn everything about Steve and the impact he is having in the AI community through his many roles at Forbes, ACS, ISO and more!   Enjoy the show! Check out our upcoming live events at datafuturology.com/events Read the full episode summary here. --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

Organisations are in constant need of innovation to fulfill their end consumer’s needs. That’s why several companies have started innovation areas to help update and grow their main business. Today we are focusing on starting a Machine Learning and AI initiative within these innovation areas to grow the value they are providing, scale their results and positively impact the rest of the organisation. We are joined by Ram Radhakrishnan, General Manager for Customer Analytics, AI & Data Science at WooliesX, where he is building world-class capabilities thanks to 250+ data practitioners coming together. Ram is certain that AI and ML are future capabilities able to take organisations to new heights, whether it be solving business problems or providing a unique customer experience. The AI & ML space is quite big and diverse, but both Ram and Felipe share how they’ve seen a huge rise in the demand for machine learning engineers due to the growing need of scaling and operationalizing models. When it comes to hiring, the most important skill he looks for in candidates is the right attitude and the desire to always keep learning. WooliesX has a focus on teams and their members and works for them to dedicate nearly 20% of their time towards developing their own skills and knowledge. Tune in for the full conversation where Ram goes into detail about WooliesX agile practices, their scope of work, growing their teams and what he believes are the most important upcoming skills in the data space. Enjoy the show! Check out our upcoming live events at datafuturology.com/events Read the full episode summary here. --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

In this episode, Felipe speaks about what is going on with artificial intelligence in the retail space. Visual search and recommendations are currently trending in retail. Companies are offering the ability for consumers to search based on a picture. For instance, consumers can take a picture of a pair of shoes and find that product online, similar products, and products that would go well with it. Humans can process images way faster than text. Plus, pictures carry more information than sound. Visual search and recommendations are hot and on the rise right now. Free shipping and free returns are hurting companies. People are buying multiple items with free shipping and then returning it. As a result, the retailer is paying for transport on both ends. Retailers are struggling with this model. However, free shipping is something that consumers are looking for. So, brands are offering a subscription model or a rental model. Sometimes, a combined subscription and rental model. More and more companies are offering clothing rentals. Next, Felipe explains what to expect in retail. Automated stores are popping up in the United States from Amazon. You pick what you want in the store; then, you walk out without having to see a cashier. With advancements in AI, the movements of customers can be tracked in retail stores. Voice assistance is also something you can expect to see in the future of retail, like ordering something using an Alexa. Stay tuned as Felipe speaks about the basics of AI in retail. Enjoy the show! --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

Christoph Molnar is a data scientist and Ph.D. candidate in interpretable machine learning. He is interested in making the decisions from algorithms more understandable for humans. Christoph is passionate about using statistics and machine learning on data to make humans and machines smarter. In this episode, Christoph explains how he decided to study statistics at university, which eventually led him to his passion for machine learning and data. Starting out studying with a senior researcher gave Christoph exposure to many different projects. It is an excellent program for students and companies whom both benefit greatly. Christoph learned so much about statistics that he would not have been able to acquire otherwise. The clients got nine hours of consulting for free, which is very valuable for their businesses. When Christoph started his statistical consulting career, he did patient analysis to assess if a medication was affecting the spine. He found this very interesting as it differed significantly from his previous consulting. When labeling data, Christoph says to label and always compare continuously. For instance, when a student labeled one photo, later on, Christoph would show a student the same photo and see if it got labeled identically. Sometimes people will see the same image but label it differently; so, this is one thing you can do to ensure labeling data is going smoothly. If you have multiple labelers, you will need to compare how each labeler will mark the same photo. Do not be blind to the quality of your data; it is easy to adjust the numbers. Then, Christoph speaks about pursuing his Ph.D. in Interpretable Machine Learning. He publishes his book, Interpretable Machine Learning, on his website chapter by chapter. Christoph gets feedback and uses it while continuing his writing on future chapters. Learning about interpretable machine learning is not exactly present at university now. Some schools and professors are starting to integrate it into the curriculum. Stay tuned to hear Christoph discuss accumulated local effects, deep learning, and his book, Interpretable Machine Learning. Enjoy the show! --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

Steve Monaghan is the Chief Digital Officer at Riyad Bank. He has a series of investments in banking and insurance using AI and new technologies in order to improve efficiency. He started out as a commercial pilot working 22 hours a day, running the aviation company during the day and flying at night. His first contact with data came when he started using spreadsheets to automate tasks and accelerate the time in which he got them done. He was able to quote 3 days before any of his competitors and his business boomed. This gave him a great insight on the impact technology can have. His career then moved from flying into technology. Within this industry, he has learned that people have a learning curve and for them to adopt change, they first need to understand it. You need to show people how processes and systems work for them to understand and accept them. That’s the reason why he thinks curiosity is such an important trait. For Steve, the three core laws of technology that drive data science and AI are: Moore's Law: processing power doubles every 18 months for the same cost. Metcalfe's Law: the value of a network grows by the square of the network's size. Kryder's Law: storage doubles every 13 months for the same cost. He believes these 3 laws encompass the ability you have to assimilate learning into knowledge. The faster you do that, the bigger the advantage you have over your competitors. It’s almost as if you live in their future because you’ll be able to see things they won't see for a period of time. Stay tuned to learn more about the impressive way he looks at what you can do with technology, the results he’s had and how he leverages AI in business. Enjoy the show! --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

Stuart Long is the CTO Hewlett Packard Enterprise. In his role, he identifies different product portfolios and pulls together solutions for different customer sets, such as public health, education, finance, retail, mining, and determines how to develop the solutions from HP’s product portfolio across all the different stacks. In this episode, Stuart tells us how HPE are moving the analytics to the edge, making it actionable with the ability to link data across the organization and across multiple organizations with a new solution out of Europe; Gaia X.  He says that with today’s privacy regulations, it’s now about federating your data and then making that data available to people but still within your control. But you can’t do it alone – you need an ecosystem of partners and products to do that.  And that’s exactly what HPE has done. They have built a whole range of products to do what they call ‘federated data analytics’. This allows you to look where your data is and start to then understand where you want to analyse that data, and what data flows you need to provide, and how you want to basically store and categorize that data. There are a number of what they call “architectures”, and underneath those architectures, they are developing products that fit nicely within those to enable the customers to look at how to deploy these new systems. Finally, Stuart tells us what excites him most about the opportunities ahead for Gaia and the data economy as a whole and HPE’s plans for Gaia in the next 3-5 years.  He says the ability to see a whole new range of services be made available very quickly, and different ways of utilizing those services - is what he calls ‘service chaining’. Giving the consumer a way of being able to choose from multiple different providers and customize their own different services and chain them together. Stuart believes it’s really about developing the whole ecosystem and bringing on different partners.  We will start to see more edge to quarter cloud type environments where organizations will now have a lot more edge processing. Companies will become more and more digital, and services will become more and more digital. He tells us that there will be some interesting opportunities for organisations and with this level of innovation, there is going to be good and bad, but it’s about making sure that you can optimize the good and limit the bad. Enjoy the show! Read the full episode summary here. --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

Organisations work hard on creating and building data science capabilities and models that will provide a real positive impact for their users. However, the feedback we’ve had from the Data Futurology audience shows there is a struggle to get ROI from their AI. So what do you do when your models and AI efforts are not living up to their promises? This conversation explores how to ensure that your AI projects don’t fall flat, but actually deliver business value. In this episode, we hear from Scott Hubbard, Director of HPE Ezmeral Software Business Group, South Pacific and Ridhav Mahajan, Solutions Engineering Leader, HPE Ezmeral Asia Pacific. They have recently been part of setting up a start-up within HPE, that focuses on cutting-edge stacks in the AI, ML and data space. Though this startup is fairly new, the technology behind their platform, Ezmeral, has been in production for over 10 years now! One of the current challenges organisations face is accessing all of their data. Whether it’s stored in silos in the cloud or on-premises. As data grows exponentially, being able to scale a platform almost infinitely to keep up with that demand is a vital aspect. To address this, they have worked on what they call Data Fabric, a layer under a data platform with the ability to unify data sets across an organisation and bring data silos together so you can have a single data source. Tune in to hear Scott and Ridhav expand on the adoption of AI in an organisation and share their industry experience with us. If you want to learn more about leveraging your data with AI, join the HPE Ezmeral Asia Pacific Launch to hear our host, Felipe Flores, share his insights on Getting Value From AI At Scale. Save your spot here!  Enjoy the show! Read the full episode summary here. --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

If you are trying to choose what skills you should build as part of your career, no single answer fits everyone. It depends on your strengths and ambitions. Your strengths are the things you are naturally good at. If you're not sure what your strengths are, then think about the things that people come and ask you about. When someone asks you how you do something, most likely that is one of your strengths. Also, think about where you want to end up in your career. For instance, if you're going to become a manager, find a way to be a leader on a project and develop your soft influence. Hard influence is something that comes from authority. Whereas soft influence is something that we can build upon. Find a way to lead a project among your peers. Taking the lead will allow you to practice your influence, leadership, and management skills. A group of people will follow the person with an organized and well-thought-out plan; be that person! Another tip - do not be the person that blindly follows what they enjoy; it's not a strategic way to go about crafting your career. Felipe has seen people have a successful career doing work that they enjoy. However, they will eventually lose their love for it. Plus, if you only follow what you enjoy, then you run the risk of getting pigeonholed in an area that may not have future growth. Also, it might be an area that loses demand and importance; it can make your skills irrelevant. At the end of the day, we need generalists. Companies need people who are knowledgeable in the end to end process. As an industry, data scientists are in high demand. Plus, they need people who have a mix of skills. There are always more roles being added because the industry is starting to understand that a great deal of knowledge is required to build a successful data science team. Enjoy the show! Read the full episode summary here: Ep 108 Thank you to our sponsor, Talent Insights Group. --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message