Happy Birthday TWiML!!!

877 265 This Week in Machine Learning & AI

May 20th was the one year anniversary of This Week in Machine learning & AI. I started this podcast last year as a way to share what I was learning about the field, and to be quite honest, I really had no idea what I was getting into. But what an amazing ride it’s been. The amount of interest in the podcast has been incredible, and I could not be more appreciative of, or impressed with, the TWiML listener community. Thank you so much!!! We’re working really hard to be worthy of your attention by continuing to bring you amazing content you can’t find anyplace else. 

Update: I’m super excited about the amazing community we’re building around the podcast and I appreciate you all very much! Thank you so much for kind words and gracious comments as we celebrate this milestone for the podcast!

73 comments
  • Asha
    REPLY

    This podcast IMO spreads Awareness of how technology is evolving with ML and AI. It helps to up to date on what are different forms in which ML and AI is getting applied across the globe and how, along with data, it is changing the end user experience. Thanks for helping us with this.

    I joined this podcast recently and my favourite moment has been the statement by Ruchi where he says ML for ML and don’t ask the consumer which algorithm they want. It is becoming so true with the demand for ML being used by every other organisation.

    • Yaron Blinder
      REPLY

      TWIML talk is a fantastic source of both technical knowledge and human perspective in the ever-accelerating field of machine learning and AI.
      When I started listening, I was a fresh PhD graduate in biomedical engineering making a transition towards data science. Today I am Co-founder and CEO of a medical AI company, and many lessons I learned through TWIML have been instrumental in this journey!

      Thank you Sam for your great work on this.

  • Ned
    REPLY

    I decided a few months ago to start some self-paced online learning in the fields of machine learning and artificial intelligence, looking to eventually delve more specifically into deep learning and neural networks. I just discovered your podcast a few weeks ago and have been enjoying it each week, though I still need to work through all of your past episods. I love the interviews with people using ML and AI in interesting or non-obvious ways, like Scott Stephenson’s audio work and Stefano Ermon’s work on sustainability projects.

    Keep up the great work! Also, congratulations on your podcast surviving its first ~940 million kilometer trip around the sun!

  • Nikhil Makkar
    REPLY

    Congratulations Sam and Happy Birthday TWIML &AI
    After starting my Master’s in 2016, I came to know about Machine Learning. Now I am working on Computer Vision. Your Podcast provides a broad view of what is happening in the world of Machine Learning and AI and also give insight into some topics.

    I loved the podcast with Matt Zeiler as he provided insights into the Layers of convolution neural networks. Also, the podcast with Dominique Simmons as it broadened my view of Machine learning into the Natural Language Processing and its challenges. And yes, the talk with Pascale Fung about robots with empathy was very interesting.
    One of the best things I found about your Podcast is that you always try to bring people from various domains working on Artificial Intelligence like Systems people, Cognitive Psychology people, Physicists, Computer Scientists etc.

    My favorite quote ‘Deep Learning is not deep enough’. I don’t remember the episode but this quote is so strong that I can’t forget it.

  • Vishnu
    REPLY

    Happy Birthday TWiML, hope this show goes a long way like other great tech podcasts. I just started with TWiML about three weeks ago and the experience have been great.

    All the Best Sam!

  • Thomas Le
    REPLY

    Sometimes in February, I found your podcast while searching for something to listen to during a lunch break at work. I did not have any background in machine learning (ML) or artificial intelligence (AI); I just wanted to find a podcast on my phone to keep me company in the company’s empty break room (P.S: I start my workdays at 6AM, and I eat my lunches at around 11 AM, which is still early for most of my coworkers).

    After that first encounter, I started listening to your podcast regularly. Your podcast helps increase my interest in ML. Your podcast also played an important part in my decision to take the online Machine Learning course taught by Professor Andrew Ng.

    I still have a long way to go and a lot more to learn in ML. I believe that your podcasts will be a great companion in my journey into ML.

    Doing a podcast takes great dedication. Maintaining great contents that keep listeners tune in week after week requires tremendous commitment. On the birthday of your podcast, thank you for your dedication, and congratulations on your success.

  • Andrew
    REPLY

    I’ve used this podcast to maintain a pulse on current ML & AI. Big thank you for both helping me in my day-to-day, but also getting me interested in ML in general when I first started listening. Heck, I’ve been listening to this podcast when I was a student, then when I was an intern, and then when I was a entry level analyst, and then when I was promoted to analyst, and now as a senior analyst. Where I am now is in no small part thanks to this podcast.

  • Randy
    REPLY

    My favorite episode of TWIML is actually I think the first or second episode I heard. I started on the podcast back in December and heard Francisco Webber talking about Cortical.io and natural language processing. I’ve always been interested in NLP but didn’t have a good idea of how to represent words as numbers. The cortical.io method of using sparse distributed representation is a unique and interesting method. After hearing the podcast, I started into research about Hierarchical Temporal Memory (HTM) and its founder, Jeff Hawkins. I downloaded Jeff’s audiobook, “On Intelligence”, and listened to that. I believe that this is going to be THE KEY area in Aritificial Intellingence. I believe it has potential way beyond what deep learning can achieve. I’m now writing my own code using the HTM algorithms to understand & demonstrate how ML methods can be applied to actual brain processes. I’m re-invigorated by the discussion that I heard on your podcast and I am making great progress towards my own investigation and research. Thank you for such an interesting podcast. Congratulations on your one year anniversary!

  • Bruce
    REPLY

    I have enjoyed the podcast and tend to look forward to it weekly. With your offer, I finally reached the point where I thought to comment. I have mentioned it to a few friends and I hope your listener-ship is constantly on the rise. Keep up the interesting interviews, they all have unique perspectives on ML/AI.

    Cheers
    Bruce

  • Chang Xu
    REPLY

    Happy birthday TWiML! I’ve loved listening to your podcasts since I found it in Jan. I’ve especially liked how you profiled the early stage but fascinating AI startups in the AI NexusLab. Keep up the good work!

  • Alex
    REPLY

    I worked with Fuzzy Logic and Artificial Neural Networks about 20 years ago with a researcher while in college where we worked with Intel 80386 CPU’s to train ANN with Back Propagation and other algorithms to make predictions. Then I got in the networking industry and last year I noticed the advances in computer architectures as well as in ML & AI techniques enabled the application of them to solve real problems. I found the TWiML&AI podcast while I was looking for resources to catch up on the latest advances in ANN and after comparing with other sources I was convinced this is the best resource to know what engineers and scientists are working on in the fields of ML and AI. One of the talks that engaged me with the podcast was the one with Dr James McCaffrey on “Understanding Deep Neural Networks” that inspired me to come back to work on this interesting field. The talk about “Statistics vs Semantics for Natural Language Processing” with Francisco Webber inspired me to go deeper into thinking out of the box while further reading the resources suggested including the “On Intelligence” book by Jeff Hawkins. Something that I noticed is that people misunderstand and underestimate the capabilities and the ML & AI technology, therefore, this podcast is filling a gap to inform people and expand the use of ML & AI to solve difficult problems.

    Congratulations to TWiML&AI for this first year and thank you for the dedication in producing a well structured and excellent quality podcast.

  • crcons
    REPLY

    I’m only here for the stickers. Gimme the stickers! 🙂

    But in all seriousness, I’ve started following the pod just a few weeks ago, determined to get more knowledge in ML and AI, and it has been a huge incentive as much as a great source for information in what’s happening in the world of Machine Learning. I live in Brazil and there aren’t many conferences on the subject around here, so if I want to get to know the most recent researches and get inspired on how to use my ML knowledge, TWiMLAI is one of my few resources, and such a valuable one, I must add!

    I have some little background on cognitive studies, so the recent interview with Dominique Simmons was particularly inspirational to me, but the one I liked the most and that I recommended to several of my friends was the one with Deepgram’s founder Scott Stephenson. What a story! Regardless, all of the episodes bring useful information, insights, and lots of inspiration.

    Congratulations on the first podversary of TWiMLAI, and may many others follow! And thanks for the service you make for this community, Sam.

      • crcons
        REPLY

        I don’t know why anyone on their right mind would want to learn Portuguese, but you’re doing very well! 😀
        I’m sure that you’ll find no shortage of potential interviewees to your quest! The field of Machine Learning is in a rise here in Brazil.
        Btw, thanks for the hint on the PAPIs conference. I don’t think I’ll be able to make it to there – I’m based in Porto Alegre, but I’ll take a look.

        • sam
          REPLY

          Ha! I’ve never met a language that I didn’t want to learn, and I’m slowly making my way around to all of them. If only I could remember anything of the ones I’m not currently studying I’d be golden!

  • Sidharth Ramachandran
    REPLY

    Wow – I didn’t realize that TWIML is only a year old. What a fabulous job getting here so soon. Your podcasts have always been enlightening and inspiring. The guests seems to have achieved so much in their professional careers but yet humble enough to share their learning.

    Great job and looking ahead to the next many years!

  • Jeff
    REPLY

    Congratulations on doing this for a year. I think this is one of the few podcasts I make time for to listen to every week.
    The interview format with practitioners in the field from a wide range of experts in the ai /ml world is great. I think your skill as an interviewer helps as well. Whenever I am thinking of a follow-up question I’d like to hear, you tend to ask it. You also don’t allow too much hand waving without at least some specifics and examples. Getting interviewees to go into the weeds really makes this podcast great.
    Congratulations again and thanks for doing this work. It truly adds value to the field.

  • Joao Goncalves
    REPLY

    Hi, Sam.
    To say that this podcast changed my life would be an understatement. A couple years ago I started college. In the beginning, it was exciting, as starting new things usually is, but as time went on I gradually discovered that electrical engineering wasn’t something I was passionate about. In my spare time between classes, I took the time to learn java and got into programming quite a bit. I have always considered myself a very logical person, and the thought process required to deal with programming hurdles seemed to match me quite well. Plus, I have always been drawn to the prospect of, in some way, being able to potentially affect millions of people for the better. This is something that feels much more within the grasp of a programmer than somebody in another area of studies could hope to.
    Now, at the end of the school year in June-ish 2016, i came across your podcast. At the time I was familiar with the term ‘machine learning’, but only because I had heard the term thrown around several times. I didn’t have a deeper understanding of it. As I delved into the podcast, my interest in it and AI grew exponentially. I looked into Andrew NG’s Coursera lessons, I read about neural networks and what they are being used for, what they can be used for in the future. I got acquainted with Google’s APIs (Cloud Vision, Translation, Audio Transcription, etc). I found a passion for this subject that I never knew I had in me, and I wish to pursue it fully as I continue my studies, and further after completion of those.
    It didn’t strike me at the time, but looking back I can say almost certainly, that this podcast was the catalyst of it all. And for that, I have to thank you (Thank you).
    As I look at how things are now, I realize that the coming years will be the golden years. Both in my life, as I undertake this new path in personal development, and get to know new people in the field, but also for AI. This is the point where we as a species will start exponentially taking more advantage of the new capabilities of advancements in artificial intelligence for the betterment of Humanity. And TWiML will follow this development. As we optimize crops for soil longevity and maximize efficiency, solving the global food crisis. As there’s a major breakthrough in cancer research. As the singularity is slowly being gestated in the transistors of supercomputers around the globe…
    Here’s to the next years of TWiML&AI, and to the future.
    Cheers,
    Joao

  • Mark Trovinger
    REPLY

    As a aspiring Data Scientist/ Machine Learning Engineer, I have found your show to be incredibly inspiring! From the earlier shows that helped keep me up-to-date about what was going on in this very fast paced field, to the switch in format with guests that allowed for a deeper look at some very important aspects of actually working in Machine Learning and AI, I have found your show to be absolutely top-notch and I recommend it to anyone who has even a passing interest in ML/AI. The guests you have had on talking about getting started, such as Clare Corthell, to building one’s confidence as Siraj Raval did in his time on the show had given me confidence to continue in this field. The guests who have talked about actually taking the step from concepts to an actual working product have been incredibly helpful as well. I look forward to seeing the show continue to grow!

  • Niels Leadholm
    REPLY

    This show is brilliant. I’m a medical doctor working in the UK but in a few months I’ll be starting a PhD in Oxford in artificial intelligence and Sam Charington’s podcast has been a great way to broaden my awareness of the field’s reaches.

    All the episodes are great, but probably one of my favourites was the interview with Brendan Frey. As elaborated in the show, biology is unfathomably complex, and I thought the approach they are taking to understanding genetics is a really exciting new interpretation. It always impresses me that Sam is able to ask interesting questions of his guests no matter how disparate their domain may be.

    Please keep it up!

  • Ingrid Serrano
    REPLY

    Happy Birthday TWiML&AI!

    I discovered this podcast a few weeks ago and I am hooked. I am working my way thru all the back shows. It is a great resource to keep up with what is new, listen to expert’s opinions and learn about exciting projects. It is informative and inspirational. I particularly liked the interviews with Kathryn Hume and also Xavier Amatriain due to their insights on the practical approaches and applications of ML.

    Thank you for bringing this great resource to the community. Keep up the good work!

  • Connie
    REPLY

    Congratulations on 1 year, TWiML! This podcast is one of the few that keeps me listening every week! I particularly love the wide range of research areas of the guests on the show. One of my favorites has to be the interview with Brendan Frey from Deep Genomics. Reverse-engineering the genome is a fascinating application of deep learning since biological processes are just too complex for traditional ML models like linear regression and HMMs. By training deep neural nets jointly for each biological process, multitask training can be used to map DNA sequences to phenotype. Very cool research area with great promise in fighting disease and genetic disorders.

    I love the format and am looking forward to many more years of TWiML 🙂

  • Court Haworth
    REPLY

    When I first discovered the podcast last summer, I was a student finishing up my bachelors degree in Chemical Engineering but I had realized that I didn’t want to stay in the industry. After doing some internships in data analytics that I found interesting I was considering going into a more data intensive career. Listening to the podcast provided me with a wealth of information about what is possible through machine learning and AI. The diverse range of speakers offering lots of interesting insight made it very clear to me that I was fascinated by the potential of machine learning. I am now about to start a Masters program in Data Science and hope to transition into a career where I too can use machine learning to solve interesting problems. The podcast really helped me figure out what it is that interests me and I am so thankful for the podcast and everything it has allowed me to learn. Looking forward to many more!

  • Justin
    REPLY

    I listen to your podcast regularly and find your interviews engaging and accessible. As a product manager who partners closely with data scientists, your podcast has helped me be more empathetic to some of the challenges my DS collaborators face, but also to suggest new opportunities to push boundaries. I also appreciate that you address a broad range of topics and that your guests are some of the best and brightest. Keep up the great work!

  • Vk
    REPLY

    I’m Data scientist who, finished his masters about a year ago, works with deep learning very frequently. For several (“big”) application we need very fast compute (both for training and inference).

    I would say Shubho sengupta’s episode would be my favorite. His interview touched on a number of topics that my research group and I have seen and struggled with. Such as public datasets for large scale sparse signals (e.g. audio). He managed to concisely and cohesively cover the “overfitting” of deep model infrastructure to vision based (convolution, large matrix mul) models. Something that is not highlighted often enough in the hype surrounding deep learning and GPUs.

    There were also lots of interesting things we learned. For example the speed of light metric was especially interesting.

    All in all TWiML has been excellent. Without it

  • Vk
    REPLY

    I’m Data scientist who, finished his masters about a year ago, works with deep learning very frequently. For several (“big”) application we need very fast compute (both for training and inference).

    I would say Shubho sengupta’s episode would be my favorite. His interview touched on a number of topics that my research group and I have seen and struggled with. Such as public datasets for large scale sparse signals (e.g. audio). He managed to concisely and cohesively cover the “overfitting” of deep model infrastructure to vision based (convolution, large matrix mul) models. Something that is not highlighted often enough in the hype surrounding deep learning and GPUs.

    There were also lots of interesting things we learned. For example the speed of light metric was especially interesting.

    All in all TWiML has been excellent. Without it car rides home would be that much more boring and my feel of the pulse of ml much, much worse. Great work and thank you!

  • Mason
    REPLY

    Hey Sam,

    The show is fantastic! I started listening right when you switched to the interview format, and I’ve definitely noticed your improvement as a journalist and the improvement of the show. Great job! I go to school in Boston, so the show keeps me company on my 20 minute walk to school every morning and I couldn’t ask for a more interesting companion. I’m studying analytics, and while I may not directly use AI in my profession, I certainly use it as a hobby.

    I really enjoyed Carlos Guestrin when he came on to talk about the LIME paper, and the Danny Lange discussion about video games.

    Thanks for all you do Sam!

  • Sebastian
    REPLY

    I’ve been following this podcast since august 2016, and listened through all the episodes. The podcast has evolved from a purely informational one to these dedicated interviews. As a ML practicioner for the past 10yrs, i appreciate both the production effort as well as the topic quality. I look forward to another year of fascinating and dedicated podcast episodes, and I certainly hope to have the chance to contribute. Thanks for all the hard work Sam, to another year!

  • Vijay Natarjan
    REPLY

    Dear Sam,

    Many Congratulations… Wishing HAPPY Birthday to TWIMLAI. It is been wonderful looking forward for the podcast week after week.
    I have been an addict to your podcast. When I was introduced to this Podcast by my Colleague, I got glued. It blows my mind when I start to realize that this podcast comes miles crossing oceans, still fells that you are in deep conversation with me. I felt It is nice way to keep abreast with Technology.

    Your podcast motivated me to be self learner, Podcast Talk #1 Clare Corthell Opensource Data Science motivated me to become Learner in Machine learning. I went ahead to complete Andrew Ng’s Machine Learning (Stanford online) and Deep Learning Nano degree Foundation from Udacity. After 21 years it was possible for me to take quizzes and projects to complete the course. Now I’m proud to say that all happened because I was in touch with you.

    Thanks so very much, much appreciated all the good work !! Again wishing TWIMLAI Family Happy Birthday.

  • Johan Boesveld
    REPLY

    Happy Birthday TWIML&AI

    In ML and AI a year is quite a long time and for me this podcast is one of the best ways to keep updated. Although I’m not a hardcore data scientist, I am very much interested in what implications ML and AI have and will have to our society, to science in general and to ourselves as human beings.
    I only started to listen in January and I am still working my way trough the older episodes but every episode of TWIML&AI broadens my horizon. I really like how TWIML&AI shows us in depth how different fields of science, that were separated before, nowadays get connected through ML and AI. I also really like the length of the interviews that enables you to dive deep enough into the subject to get a good understanding of it. Again and again, I end up with a bunch of names, notes and ideas that inspire me to investigate further
    It’s hard to pick a favorite episode but the recent story about how similarities between analog particle physics and audio have lead to the creation of Deepgram is still on my mind.

    So thank you Sam for your inspiring work or “Chapeau!” as we would say here in France.
    I’m really looking forward to a new year of TWIML&AI

  • Vijay Natarajan
    REPLY

    Dear Sam,

    Many Congratulations… Wishing HAPPY Birthday to TWIMLAI. It is been wonderful looking forward for the podcast week after week.
    I have been an addict to your podcast. When I was introduced to this Podcast by my Colleague, I got glued. It blows my mind when I start to realize that this podcast comes miles crossing oceans, still fells that you are in deep conversation with me. I felt it is nice way to keep abreast with Technology.

    Your podcast motivated me to be self learner, Podcast Talk #1 Clare Corthell Opensource Data Science motivated me to become Learner in Machine learning. I went ahead to complete Andrew Ng’s Machine Learning (Stanford online) and Deep Learning Nano degree Foundation from Udacity. After 21 years it was possible for me to take quizzes and projects to complete the course. Now I’m proud to say that all happened because I was in touch with you.

    Thanks so very much, much appreciated all the good work !! Again wishing TWIMLAI Family Happy Birthday.

  • Bernardt Duvenhage
    REPLY

    Hi Sam

    Thanks for an awesome podcast! I’m fairly new in an NLP job and have been binging your episodes over the last couple of weeks during my morning commute to great effect. I also regularly go back to you show notes! Thanks for that.

    Regards
    Bernardt

  • Michel Jacquemin
    REPLY

    Happy Birthday TWiML&AI !

    Having taken several online courses in ML, participated in a few Kaggle contests, and read a few papers on the subject, I really enjoy listening to this podcast regularly, to get a sense of who is currently doing what in ML and AI, and of what the trends are.

    Congratulations Sam, thank you, and keep them coming !

    Michel

  • Bill Berrien
    REPLY

    At first I didn’t like the switch to the extended interview format as I valued the broader weekly update on ML news (and I gave the podcast a lower rating on iTunes because of it – 2 stars). Since then, however, I have really grown to enjoy and value the long interview format (and I subsequently raised my iTunes rating accordingly, now to 5 stars).

    I particularly enjoyed the Deepgram interview. It showcased well the portability of ML techniques across disciplines.

    Overall, excellent podcast that has encouraged me to subscribe to ML /AI courses (and their prereqs) on Udemy and start to acquire additional insight.

    Thank you!

    Bill

  • Tirthankar
    REPLY

    Dear Sam,

    Warm Congratulations on the anniversary. Cheers!

    The podcasts has been best-of-class, very informative, and for me triggers new avenues of learning. I feel to be in-sync with the global tech developments with a practical bend in the exciting areas of ML & AI. This has enriched me greatly.

    Thanks and many many happy casts ahead.

  • Alexander Tolpygo
    REPLY

    I think a lot important and often intangible contributions are made by hosts and guests that have a broad influence on listeners; we can see the results and impact in some of these comments alone. It’s important to both support and congratulate the efforts you’ve made and the impact that you’re creating with data science and the open data science community. Best of luck in year two and hope to speak at Strata.

    Best,
    Alexander

  • Ankur Patel
    REPLY

    TWIML, congratulations on the first year anniversary! I have loved listening to the show. I remember the news in machine learning from the first few months – what a sheer amount of information. But, the more recent interviews format is excellent. I particular love the ones where you interview folks at AI/ML conferences. Very insightful, indeed. Thanks for contributing to the greater ML community. We need more people like you.

  • Paddy Benson
    REPLY

    Happy Birthday TWiML&AI.

    I started listening in June last year when I took over responsibility for a bunch of Data Pipeline and BI teams. Its been super interesting and i have learned a lot. Thanks for keeping it going Sam. I have especially enjoyed the interviews and in a space where so much is happening its been great to have a news digest and have you separate the wheat from the chaff.

    Thanks and Happy Birthday!

  • Brad Miro
    REPLY

    Hi Sam,

    Congratulations on a successful first year with the podcast! I started listening to the podcast back in March from the very first episode and I’m nearly caught up. As an entrepreneurial-minded developer, it’s been incredibly interesting to me to hear about how ML is used in the industry, and what works and what doesn’t. Your interview with Charles Isbell got me interested in the OMSCS from Georgia Tech and I’m thinking of applying!

    Thank you for providing the ML/AI community with an interesting and insightful source of information that allows new practicioners (such as myself) and professionals to gain perspective on the field from others who have experienced building ML systems and companies first-hand.

    Here’s to another successful year!

    Best,
    Brad

  • Nikola
    REPLY

    Happy Birthday TWiML! I started listening at the end of last year. At first, I wasn’t sure what to think when the format of the podcast changed but now I feel like I actually enjoy the interviews more. It’s a great way to hear from people in the industry, especially because I’m rarely able to attend a conference – there is not much going on in my area.

    Thank you and good luck in the future!

  • Quang
    REPLY

    TMiML&AI is one of my favorite podcast because of the quality of its information. It contains just enough level of technical and opens the conversation with so many industry experts, something that the major of us wouldn’t have a chance to do. One of my favorite podcast is the interview with Charles Isbell. I actually consider leaving work and getting back to grad school, and that episode is on point. Each episode is an inspirational story that motivates me on learning more about this field.

    Thanks for building this community Sam, looking forward to another excited year!

  • Robert Sidick
    REPLY

    TWiML&AI allows me to stay up to date on the latest trends in ML & AI. The interview format allows me to hear insights from actual practitioners that are helping to address real-world challenges. Even if a topic does not align with my current focus, the interviews are still engaging and valuable. Keep up the great work.

  • Talib Morgan
    REPLY

    As an independent consultant who is fairly new to machine learning, I find the TWiML & AI podcast to be one of my most valuable resources for understanding how data science practitioners are making use of data. From data analysis system architecture to the intricacies of specific ML techniques, it’s all covered. I feel wiser because I know what these things are now and have a firmer handle on how they might fit into the solutions my clients need. Great stuff, Sam!

  • Uri Tzikoni
    REPLY

    From all the AI podcasts I’m listing to, this is my favorite by far! I believe that the secret is in the balance, where non-geeks can enjoy the AI world too.

  • Kamal Gelya
    REPLY

    I’m a newbie to the AI/ML world and just started listening to your podcast (last week’s episode w/ Danny Lange). Thanks to #aiplaybook (http://aiplaybook.a16z.com/docs/reference/links) and @mattfogel (https://medium.com/startup-grind/the-10-best-ai-data-science-and-machine-learning-podcasts-d7495cfb127c) leading me to your podcast. Keep up the great work, love the non-geeky conversational style interviews. I hope to continue to listen and keep up to date. Thanks !

  • Kendra Paolitto
    REPLY

    Congratulations on your first year anniversary! As a technical and financial recruiter I started from ground zero and was charged with finding the best deep learning scientists and engineers. I started listening several months ago and your podcasts have been a helpful tool in my learning process. I particularly enjoyed Matthew Zeiler’s talk on CNNs. I’ve been inspired to partner with a cognitive neurosychologist to have more fun with AI/ML/DL recruiting.

  • Kendra Paolitto
    REPLY

    Congratulations on your first year anniversary and stepping out to start something new! As a technical and financial recruiter, I started from ground zero and worked on a client site to find the best deep learning scientists/engineers. I started listening several months ago and your podcasts have been a helpful tool in my learning process. I particularly enjoyed Matthew Zeiler’s talk on CNNs. I’ve been inspired to partner with a cognitive neuropsychologist to have more fun with AI/ML/DL recruiting!

  • Doug Kelley
    REPLY

    This is a great podcast that really helps spread the word about new techniques and applications of machine learning. Hearing directly from the people who are building things with the tools is a great way to learn.

    Thanks for making this resource available.

  • JEFFREY E MOREY
    REPLY

    Happy Anniversary! I enjoy twimlAI. The information you provide has been fundamental to my AI education. The open source masters was particularly educational. I also enjoyed both fast forward lab interviews.

  • Luke Landis
    REPLY

    As an undergrad with plenty of time that I can use to listen to podcasts, I started looking for something that caught my interest a few weeks ago. I came across TWiML and decided it would be good to expose myself before taking more structured classes in the coming semesters. I have found the podcast very interesting and have enjoyed the variety of guests in the show. This podcast has got me excited to continue to expose myself through other outlets so that I am better prepared for my actual school work. Thanks, and I look forward to being a continued listener!

  • Guy de Carufel
    REPLY

    This is a great podcast, congrats for the one year mark!

    I’ve started learning about machine learning earlier this year and have really been hooked with the crazy possibilities with ML. Your show was the very first podcast I’ve started listening too. In fact I got into podcasts thanks to your show. My favorite talks were talk #4 on training data sets, which gave a good sense of how you first need to get good data . Also enjoyed talk #12 on the human genome, which felt very intuitive, how the model is broken into segments to handle each interaction of the genome. Yet another example of how useful and ubiquitous ML can be.

    Keep up the good work, I always look forward to your next show.

  • Dominik
    REPLY

    I’m a Data Scientist by profession and really look forward to every new episode! The balance you find in your podcast between high level overviews and technical details is just amazing. I always need to think about your interview with Francisco Webber, because both of you guys made a topic, that usually needs visual explanations, very comprehensible by just talking about it. That got me and since then I’m a regular listener! Keep up the great work – twimlai is one of my main sources when it’s about staying on track with new ML technologies.

    P.S. please consider bringing back your newsletter in the podcast – missing it 😉

  • Bethann Noble
    REPLY

    This podcast has been such a convenient and enjoyable way to absorb so much activity, brilliance and diversity in the realm of ML and AI, including the diversity of applications, perspectives, experiences and points of view. The host, Sam Charrington, asks great questions and keeps the discussion going organically and productively. I have been able to absorb a lot while on an exercise machine or getting ready in the morning – without this format and the quality execution by the talented host and guests – I wouldn’t have time or attention span to pick up this knowledge. One of many cool moments – sharing favorite quotes from the fascinating guests and inspiring a quote contest. Looking forward to more podcasts!!

  • Chase Dwelle
    REPLY

    I started following the podcast after a recommendation from a friend. He is a electrical engineer and pretty into the world of ML and AI. I, on the other hand, am a domain scientist that was trying to figure out how to perform some analysis or make some predictions on a topic of interest, and the answers consistently seemed to revolve around ML and AI.

    The best thing to this podcast for me is that it provides an approachable entrance into understanding the capabilities and limitations of different aspects of AI and ML. It’s often difficult to figure out where to start when digging into the literature and many of the episodes of TWiML&AI give a perspective not only on the foundations of important techniques, but also their practical applications.

    Listening to the show has improved my learning curve for ML/AI, and I recommend it to anyone that is already in the field or interested in learning about AI.

  • Martin Chalupa
    REPLY

    Hi Sam,

    I’ve started listening just right when you switched to the new interview format and I love it. I’m software engineer and I’m not currently directly involved in machine learning or AI but your podcast keeps me updated. What I appreciate the most is your ability to do interview in a way that I can understand a topic without any deep knowledge in field. Great job. I wish you many great years and growing community.

    Martin

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