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Big Blue didn't blow it, so Marc, Shawn and special guest Matt Riley chop up the Wolverine-Buckeye game, while ML […]
Deploying Machine Learning (ML) algorithms within databases is a challenge due to the varied computational footprints of modern ML algorithms and the myriad of database technologies each with their own restrictive syntax. We introduce an Apache Spark-based micro-service orchestration framework that extends database operations to include web service primitives. Our system can orchestrate web services across hundreds of machines and takes full advantage of cluster, thread, and asynchronous parallelism. Using this framework, we provide large scale clients for intelligent services such as speech, vision, search, anomaly detection, and text analysis. This allows users to integrate ready-to-use intelligence into any datastore with an Apache Spark connector. 2020: Mark Hamilton, Nick Gonsalves, Christina Lee, Anand Raman, Brendan Walsh, Siddhartha Prasad, Dalitso Banda, L. Zhang, Lei Zhang, W. Freeman https://arxiv.org/pdf/2009.08044v2.pdf
In the podcast, I spoke with Meenakshi Kaushik and Neelima Mukiri from Cisco team on responsible AI and machine learning bias and how to address the biases when using ML in our applications. Meenakshi Kaushik currently works in the product management team at Cisco. She leads Kubernetes and AI/ML product offerings in the organization. Meenakshi has interest in AI/ML space and is excited about how the technology can enhance human wellbeing and productivity. Neelima Mukiri is a principal engineer at Cisco. She is currently working in Cisco's on-premise and software service container platforms. Read a transcript of this interview: https://bit.ly/2ZiRswO Subscribe to our newsletters: - The InfoQ weekly newsletter: www.infoq.com/news/InfoQ-Newsletter/ - The Software Architects' Newsletter [monthly]: www.infoq.com/software-architects-newsletter/ Upcoming Virtual Events - events.infoq.com/ QCon London: https://qconlondon.com/ - April 4-6, 2022 / London, UK QCon Plus: https://plus.qconferences.com/ - May 10-20.2022 InfoQ Live: https://live.infoq.com/ - Feb 22, 2022 - June 21, 2022 - July 19, 2022 - August 23, 2022 Follow InfoQ: - Twitter: twitter.com/infoq - LinkedIn: www.linkedin.com/company/infoq/ - Facebook: www.facebook.com/InfoQdotcom/ - Instagram: @infoqdotcom - Youtube: www.youtube.com/infoq
Host Dr. Nick van Terheyden, aka Dr. Nick, discusses The Great Unlock of Healthcare Data with Ribbon Health CTO, Nate Fox. Dr. Nick and Nate discuss solving the problem of navigating the healthcare system. Making sense of data from thousands of sources aggregating with AI and ML tools. To stream our Station live 24/7 visit www.HealthcareNOWRadio.com or ask your Smart Device to “….Play HealthcareNOW Radio”. Find all of our network podcasts on your favorite podcast platforms and be sure to subscribe and like us. Learn more at www.healthcarenowradio.com/listen
What's the protocol for dealing with your "friend's" leftovers? Cocktail Recipe: Cocktail: Thanksgiving Bae 1 bottle (64 ounces) cranberry juice 1 bottle (2 liters) Squirt 2 can (46 ounce each) pineapple juice 1 bottle (750 mL) tequila silver Instructions: To a large punch bowl, add the cranberry juice, pineapple juice, tequila and Squirt. Stir to combine. Add large ice cubes to chill. Garnish with fresh cranberries and lime slices. Follow Us! @cocktalespodcast @kikisaidso @coffeebeandean Check Out Our Sponsors! Sweet Magnolia Try Sweet Magnolia's skin and body products https://sweetmagnoliashop.com and use code COCKTALES Talkspace- Try online therapy today and use code COCKTALES for $100 off your first month! https://www.talkspace.com/cocktales DAME PRODUCTS- code: COCKTALES visit https://www.dameproducts.com/cocktales Try Taste Vitamins- code: COCKTALES10 ***Check our IG for Black Friday Promo codes http://tastevitainc.com/discount/cocktales?redirect=%2F%3Fafmc%3Dcocktales%26utm_campaign%3Dcocktales%26utm_source%3Dleaddyno%26utm_medium%3Daffiliate Text TALES to 64000 to get your discounted painting at https://www.paintyourlife.com Get Your Vesper! use code COCKTALES for a free engraving! https://www.lovecrave.com/products/vesper/ See omnystudio.com/listener for privacy information.
The Cloud Pod: Oh the Places You'll Go at re:Invent 2021 — Episode 144 On The Cloud Pod this week, as a birthday present to Ryan, the team didn't discuss his advanced age, and focused instead on their AWS re:Invent predictions. Also, the Google Cybersecurity Action Team launches a product, and Microsoft announces a new VM series in Azure. A big thanks to this week's sponsors: Foghorn Consulting, which provides full-stack cloud solutions with a focus on strategy, planning and execution for enterprises seeking to take advantage of the transformative capabilities of AWS, Google Cloud and Azure. JumpCloud, which offers a complete platform for identity, access, and device management — no matter where your users and devices are located. This week's highlights
We are seeing AI and ML becoming used in more and more industries, but one that seems to be a place where it is embraced with some success. From speech recognition and transcription to analyzing imaging, computers have helped medical professionals improve the care they give to patients. Just as CAD has helped manufacturers, AI systems are being used in medical research, trying to model and screen medications to try and determine which ones are potentially useful in treating various diseases. We also have used them to better tailor treatments for certain diseases, like some cancers. It seems that applying computing against vast troves of data is proving itself beneficial. Read the rest of A Strange AI Achievement
Bluemaster Laith Al-Saadi from Team Adam Levine tells tales about The Voice before laying down some mean licks, while ML […]
This week Brian speaks with Ben Stein, CEO of Staple! Relying on humans to extract, enter and manage data is a valuable waste of resources. These activities can be slow, error-prone and expensive, and worse still, no employee enjoys this sort of mundane, repetitive work. Staple has developed an ML tool that reads, interprets and extracts structured data from documents faster, more accurately and more affordably than any human can, at scale. Our data extraction capabilities operate successfully regardless of layout or language. Although business documents like invoices and receipts are common use cases for AP automation, we can an also capture data from semi-structured and unstructured documents including medical claims, bills of lading, trade settlement documentation and many more. For more information, visit www.staple.io If you have the next big idea, apply to the Expert Dojo Accelerator: www.expertdojo.com
Food is the very nourishment of life. Climate change, population growth and population density has come to challenge the way we feed ourselves. Let's look at some factors that are affecting the way we grow food:World's population is in more urbanized areas - 60% of the population lives in cities. Farms Waste Much of World's Water - On average, farms around the world account for 70% of all water that is consumed annually. Demand for locally grown food in urban areas is rising - For environmental reasons, as well as efficiency and ability to have produce that is often damaged during transport (e.g. berries)One of the emerging solutions is vertical farming and its different techniques. In this episode, we're going to talk about how it can be viable solution for highly urbanized area and in todays shift to sustainable food growth. The very way we make our food is changing.. what will the farms of the future look like? Check this episode out to find out! Materials for Content:Vertical farms are growing more and more vegetables in urban areasVertical Farming TechniquesAerofarms ImpactVertical Farms fill a Tall OrderBowery - Why Vertical FarmingSoundclips:Vertical Farming as a solution for Food of the Future - ViceThe rise of vertical farming - VPRO DOKHow Aerofarms' vertical farms grow produce - CBS MorningsFarms Waste Much of World's WaterEach degree of temperature rise, 10% of existing agricultural land will be lostHow much your food has travelled to get to your plateSupport the show (https://www.thc-pod.com/)
Contributor: Chris Holmes, MD Educational Pearls: Parkland Formula: 4 mL x [Total Body Surface Area Burned (%)] x [body weight (kg)] given in 24 hours 50% given over 8 hours and 50% given over the next 16 hours Brooke Formula: 2 mL x [Total Body Surface Area Burned (%)] x [body weight (kg)] given in 24 hours 50% given over 8 hours and 50% given over the next 16 hours 2009 military study evaluated Parkland vs. Brooke formulas for severe burn patients and found the outcomes were the same Guidelines are in flux on which formula to use, but reducing the overall volume using the Brooke formula can be done without significant change in morbidity or mortality Using fluid responsiveness by measuring urine output and signs of fluid overload can help guide overall resuscitative approach in burn patients References Chung KK, Wolf SE, Cancio LC, et al. Resuscitation of severely burned military casualties: fluid begets more fluid. J Trauma. 2009;67(2):231-237. doi:10.1097/TA.0b013e3181ac68cf Schaefer TJ, Nunez Lopez O. Burn Resuscitation And Management. [Updated 2021 Aug 11]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2021 Jan-. Available from: https://www.ncbi.nlm.nih.gov/books/NBK430795/ Summarized by John Spartz, MS4 | Edited by Erik Verzemnieks, MD ********************* The Emergency Medical Minute is excited to announce that we are now offering AMA PRA Category 1 credits™ via online course modules. To access these and for more information, visit our website at https://emergencymedicalminute.org/cme-courses/ and create an account. Donate to EMM today! Diversity and Inclusion Award
Nick Kostos gives out all of his player props for NFL Week 11. Ken Barkley tells you which teams he is betting in his underdog ML parlay for today's action. Learn more about your ad choices. Visit podcastchoices.com/adchoices
Join us this week for a fascinating discussion about artificial intelligence in neonatology with doctors Kristyn and Andrew Beam. Dr. Kristyn Beam is an attending neonatologist at Beth Israel Deaconess Medical Center in Boston, MA. She is also an Instructor in the Department of Pediatrics at Harvard Medical School. Her research focuses on machine learning applications for neonatal data with a focus on improving our decision-making in the NICU at the point of care and ultimately improving neonatal outcomes.Dr. Andrew Beam is an assistant professor in the Department of Epidemiology at the Harvard T.H. Chan School of Public Health, with secondary appointments in the Department of Biomedical Informatics at Harvard Medical School and the Department of Newborn Medicine at Brigham and Women's Hospital. His research develops and applies machine-learning methods to extract meaningful insights from clinical and biological datasets, with a special focus on neonatal medicine.Check out the show notes at: https://the-incubator-podcast.ghost.io/031-dr-kristyn-beam-md-mph-dr-andrew-beam-phd/________________________________________________________________________________________As always, feel free to send us questions, comments or suggestions to our email: nicupodcast@gmail.com. You can also contact the show through instagram or twitter, @nicupodcast. Or contact Ben and Daphna directly via their twitter profiles: @drnicu and @doctordaphnamd. enjoy!This podcast is proudly sponsored by Chiesi.
In this episode we look at can AI help me see better in a cost effective way! Grant Everybody, welcome to another episode of click AI radio. Okay, I have in the house today with me, someone I've been very excited to talk with. He and his organization reached out to me and I was quite surprised when I saw the cool AI solution that they have been bringing to the market. And Carlos has been giving me a little background on this. And I think you'll be excited to hear what it is he's putting together. But first and foremost, welcome, Carlos Anchia. You got Yeah. All right. There you go. Carlos, please, welcome and introduce yourself. Carlos Hey, Grant. Thanks a lot for having us on. Like you said, my name is Carlos Anchia. I'm the CEO of Plainsight AI. And we're bringing to market an end to end computer vision AI platform. I'm really, really happy to be here love talking about AI, computer vision, and how we can get more people to use it. Grant So okay, so tell me a little bit about what got you going down here. As you and I were just chatting a moment ago, there's so many components to AI, or it's such a broad range of technologies there. What got you thinking about the CV or the computer vision space? What problem? What How did you get started there? Carlos Yeah, that's a really good question. So like you said, AI, the breadth of AI is huge, you have deep learning, you have machine learning, forecasting, prediction, computer vision. And these are just a few. There's a lot of different applications for AI and places you can go down and succeed in. From our respect, we really, we really focus in on computer vision, specifically how to apply that to imagery and video. Today, there's a huge amounts of data going throughout the internet and in enterprise storage classes, where you can't really extract the value of that data unless you actually perform some sort of computer vision machine learning on that type of data. So we're really extracting the value of the picture or the video. So it can be understood by machines. So think of a dog and a cat in a in a picture, right? Those cases, the machine doesn't know it's a dog and a cat, you have to train it. And that's where computer vision comes in. And really, we got into it because we were pulled in by customers, customers of ours wanted to start doing more computer vision and leveraging our platform that we had around high throughput, ingestion, and event driven pipelines. So these customers came to us and hey, you know, this is great, we'd love to really use this for computer vision. And the more and more that kept happening, we kept retooling around the platform. And finally, the platform from end to end is purpose built to do computer vision technology. And it really allows us to focus in on on what we're good at today. Right? And that's really delivering value within the computer vision space. Grant So I remember the first time I wrote some of the OpenCV framework code, right. And that was my first introduced introduction to it. This is a number of years ago. And I started thinking, Oh, this is so cool. So I'm writing all this Python code, right, building this stuff out. And then I'm thinking, how many people you know, are actually leveraging this platform and look at even though open CV is cool, and it's got a lot of capability, it still takes a lot, you know, to get everything out of there. So can you talk about how you relate to that open CV? And what is it that you're doing relative to that? And how much easier do you guys make this? Carlos Yeah, so I mean, you hit the nail on the head there, right? So from a developer perspective, it's really around, I need to learn open CV, I need to learn Python, I need to learn containerization I need to learn deployments. There's a variety of different companies that, you know, they're all great in their own right, right. Every one of those companies that we just talked about organizations are contributing tremendously to AI. But from a developer's perspective, you really have to learn a little bit of everything to be able to orchestrate a solution. And finally, when you get to, hey, I use AI. Let's pretend we're looking at strawberries. Hey, look, I built a model that the Texas strawberry that is your over the moon excited, but the very next thing is around, okay, how do I take that and deploy it 1000 times over in a field across the world and understand how to make that in an operational fashion where you know, it can be supported, maintained update, and that's really where we have this this crux of an organization where it's really different building something on a on a desk for a one time use. And and there's a lot of wins through that process. But then taking that and operationalizing for business driving revenues driving corporate goals around, why would that feature is being implemented, that's really where we come in, we want to be able to take off that that single single path of workflow where it's a little bit of everything to orchestrate a solution, and provide a centralized place where other people, including developers can go and help build that workflow in a meaningful way where it's complete. Grant So operationalizing, those models, I find, that's one of the biggest, or the most challenging aspects to this, it's one thing as you know, to, to build out enough to sort of prove something out and get some of the initial feedback, but to actually get it into production. I think I saw MIT not long ago, maybe this a year ago, now, they had come out with this report, it was through the Boston Consulting Group as well, they'd mentioned something about, hey, you know, 10% of organizations doing AI are getting return on their investment. And, and, of course, when you look at all of the investment of the takes for the business to really stand up all the data scientists and all the ML work. And you can see why the numbers translate that way. So to me, it feels like not only doing this in the area of CV, but the problem you're really trying to solve it feels like is you're attacking that ROI problem, which is you could take this kind of capability into business say you don't have to stand up all of these deep technical capabilities. Rather, you can achieve ROI sooner than rather than laters. Is that Is that accurate? Carlos That's correct. And I think it's really through the adoption of technology and you hit a you hit a really strong point for us there around the the difference between it works and it's operational. That's that's really the path of your your, you're less there in the CV world and more there with the DevOps ml ops portion of it, getting machines running consistently, with the right versions of deployment strategy, that latter half of it, just as important as the model building pieces of it. But even after you get to that piece, you need a way to improve, and improvement in the model is very costly if it's not automated. Because I mean, you can just look at the the loss for a simple detector, like a strawberry, where, you know, if the model starts to perform poorly, you're not pulling as many strawberries out of the field. So you need a way to be able to update that model, quickly, get training data into a platform and push a new model back out. And it's really around how fast you can go end to end with that workflow. Again, and again. And again. And again, this is that continuous improvement that we have born into us from previous software development life, but really in in machine learning and computer vision, your ability to train, retrain, and redeploy. That is where you really get the benefit out of your workflow. Grant Well, that really confirms my experience with AI will. Typically I'll refer to the term that we've been using, as we call it a SmartStep. It's that notion that I need to be able to refactor my models and take in consideration that changed context around me, whether it comes in from the world or from the customer, or whatever that means, some level of adjustments taken place that begins to invalidate my previous AI model. And I need to be able to quickly make those adjustments. That's fascinating. How long typically does it take for you to do that kind of refactoring of your models? Is that Is it a day? Is it a year, a month? Or the answer is? Well, it depends. Carlos So it's twofold, right? So it's, it's hours to do that. But it really depends on the complexity of the model, and how long you have to train. But in an automated workflow, you're you're continuously adding data to your training set, that are lower quality predictions, where you can retrain automatically when you hit a certain threshold, and then validate the model and push that back out into your production alized environment. So it's it when you go to develop these sort of workflows. You really have to start with whatever I build, I know I have to improve on later. So that improvement cycle ends up costing a lot if it's not part of the initial discussion around how do we count strawberries, right? So it's evident you and I can nerd out on this. Let me shift the focus a little bit and ask about it from say your your customer Write from their perspective, what is it that they need to be able to do to be successful with your solution? What skills or capabilities do they have to bring to the table? Yeah, and I think it's, I think I have this conversation a lot with our clients. And it's really less about them having technology around data science and building model, and more around a collaborative environment, where organizations, you know, they have a culture of success. But that culture of success is really borne by holding hands through the fire, it's, it's being able to commit and lean in when the organization sees something that's really important to them, either either from a technical perspective or revenue perspective. And it's these companies and these types of people that get to rally around a centralized platform where they can build and collaborate with machine learning computer vision applications. And, you know, it's it's a, it's really interesting to see the companies that succeed here, because it's really based on a culture of winning, right, where the wind doesn't have to be the hardest, most technical, logically difficult problem, because complexity really drives timelines. And if you're looking to change from an organization's perspective, start getting the little wins, get the little wins, start having some adoption within the company around, wow, computer vision is working. We've identified these problems in a few hours, we have a solution deployed, you start building this sense of confidence in the organization where you can take on those larger tasks. But you have to start with a build up, you can't just go right to the highest ROI problem. No one starts at human genome sequencing. Grant Have you, or do we got a problem? Yeah. Back up, back up. So So all right. So it means to me it sounds like as an organization to succeed with this getting my problem definition, understood or crisply put together first, what would be an obvious thing to do? But how long does it take for me to iterate? Before I know that I've got value, that I've pursued the right level of the problem? You You made an interesting comment a minute ago, you're like, oh, within a couple hours, I could potentially retrain the model and have that back operationally. That means if I can fail fast, right, if I can pick my problem space, get something out there operation, try it fail fast, and then continue to iterate with AI as my helper that that's really, really quite powerful is that the model that the your person? Carlos It is the model? That's exactly right. And it's not just hours to retrain, it takes hours to start, right. And just to highlight you kind of started with, we have to define that problem set first. So even after we define that problem set, a lot of times we have to go back and redefine that problem set, and really the piece around failing fast. It's it's experimentation. And do we have the right cameras? Do we have the right vantage point is the model correct, you want to be able to cycle as fast as you can through that experimentation phase. And sometimes you have to go back and redefine that problem set. Because you're learning more as you go, right? And you're evolving into okay, I now understand the corner cases a bit better. And with the platform, you really can cycle that quickly. I mean, machine learning at scale is really how fast you can iterate through improvement. Grant It's quite, I think it's quite a testament to how the AI just world in general is improving. I know that you and I were talking earlier, years ago, you know, when I first started writing some TensorFlow code and Keras code, you know, the, the time it took to fail was much longer, right. And then the cycles were huge and, and getting this down to a matter of hours or even a few days, you know, for an enterprise's is massive. What's the, from what you've seen terms of different industries? Are there certain industries that tend to be leaning into this and adopting it or the is there no pattern yet? Carlos No, there's a there's a definite pattern. And in 2022, we'll all see kind of what that what that's looking like. And it's really an industry that has traditionally not been able to go through that digital transformation. So think of think of think of a piece that's a very manual piece, right, like physical inspection, where humans would look at something, they'd write down their notes on a piece of paper, then that that item would go through either pass or fail or some criteria for rework. That's all possible. Now with computer vision years ago, that was impossible the accuracy wasn't high enough, plain and simple. It just took it wasn't, it wasn't better than a human. Now we have models that are better than a human for visual inspection. And these industries are digitizing their workflow. So it's not only the feature of computer vision, but it's also now I have a digital record of all the transactions, I have extracted video information, it makes auditing easy for those sectors that have a lot of regulatory compliance, those that require proactive compliance to audit requirements, as well as visibility. Visibility has always been an it's funny when we talk about visibility, but it's computer vision, but like a lot of human processes, that there's zero visibility in it there, it's really difficult to audit, you know, why is this working better or not? So having that, that digitization of the flow with the feature of computer vision allows us to extract the value. And industries like agriculture are going I mean, agriculture has been a leader in technology for a while, but now you're really seeing adoption at livestock and row crop with drone technology. It's a very rich image environment, medical space, medical space for computer vision in 2022 to 2028, is estimated to be billions of dollars just with medical imaging. And that's not that's not the the total addressable market for the hardware, it's just the imaging piece. So we see we see a lot of growth in sectors that are going through this digital transformation that are adopting technologies that are now getting to the point where they can get pushed down into the masses instead of just the top five companies in the world. Grant Excellent, it seems to you part of your comment earlier made me think about process optimization for organizations, and the ability to extract processes, you're familiar with process mining, right? The ability to extract, you know, out of logs of these organizations and doing something like that where you can produce this visual representation of that, and then building models against that, to optimize your process might be an interesting use case. Yeah, that's fascinating. Carlos That's a really good point, right? Because that's, that's a different portion of AI that can be applied to like just log analysis, that then would allow you to go back and Okay, now that we have the process mind, where can we improve along the process? Grant Yeah, yeah. Amazing. So many uses and use cases around around this CV area, for sure. So let's say that someone listening to this wanted to learn more about it, where would they go? How would they? How would they find more about your organization? Carlos You can find us everywhere, right? We have a website, plainsight.ai. We're all over LinkedIn, we have Twitter, we're on Reddit, we have a Medium blog, there's a Slack channel where we geek out around computer vision use cases and how we can improve the world through computer vision. We're really we're really out there and feel free if you have questions come reach out to us. We have amazing staff that are looking to empower people in AI. So if it's through just just a question around how does this thing work, we'd love to talk to you if it's Hey, we're kind of stuck in our journey. We need some help reach out to us we can help you. Grant That's awesome. Carlos I can't thank you enough for reaching out to me and for a listening to click AI radio, but also for reaching out and sharing what it is you are you and your organization are bringing to the market think you're solving some awesome problems. Carlos Thanks a lot, Grant. Appreciate it. always appreciated talking about computer vision and AI and thank you to you and your listeners and really appreciate what you're doing to the AI space. Grant Alright, thanks again, Carlos. And again, everybody. Thanks for joining and until next time, go get some computer vision from Plainsight.
Host Health Beyond Healthcare and The Medical Data Navigator with Digital Health Futurist, Maneesh Juneja. Dr. Nick and Maneesh have common passions in sensors, wearable and intermittent fasting. They discuss the more data input to healthcare decision making and using AI and ML to analyze and provide insights. To stream our Station live 24/7 visit www.HealthcareNOWRadio.com or ask your Smart Device to “….Play HealthcareNOW Radio”. Find all of our network podcasts on your favorite podcast platforms and be sure to subscribe and like us. Learn more at www.healthcarenowradio.com/listen
In the widely circulated article “The Cost of Cloud: A Trillion-Dollar Paradox,” venture capital firm Andreessen Horowitz showed how the rush to public cloud IT services can eat away business valuation over time. In this Tech Barometer podcast segment, explore the real cost of running a business on public cloud with Martin Casado, general partner […]
After reviewing federal regulators' traditional theory of redlining, we discuss the types of underwriting practices that are likely targeted by Director Chopra's recent comments expressing concern about “algorithmic redlining”, examine how the use of machine learning (ML) underwriting models incorporating alternative data can be more inclusive than traditional logistic regression models and result in more approvals for protected class members and “credit invisibles”, and offer our thoughts on actions that technology and credit providers should take in response to Director Chopra's comments when developing and using ML models. Alan Kaplinsky, Ballard Spahr Senior Counsel, hosts the conversation, joined by Chris Willis, Co-Chair of the firm's Consumer Financial Services Group.
In this Intel Conversations in the Cloud audio podcast: Nitin Somalaraju from Tech Mahindra joins host Jake Smith to talk about the company's Speech Analytics platform named Sayint, which uses cutting-edge artificial intelligence (AI), machine learning (ML), and natural language processing (NLP) to uncover meaningful insights from customer conversations. Nitin talks about why regional localization […]
YouTube link: https://youtu.be/Z0TNfysTazc Sponsors: https://brilliant.org/TOE for 20% off. For Algo's podcast https://www.youtube.com/channel/UC9IfRw1QaTglRoX0sN11AQQ and website https://www.algo.com/. Merch (until end of Oct 2021): https://tinyurl.com/TOEmerch Patreon: https://patreon.com/curtjaimungal Crypto: https://tinyurl.com/cryptoTOE PayPal: https://tinyurl.com/paypalTOE Twitter: https://twitter.com/TOEwithCurt Discord Invite: https://discord.com/invite/kBcnfNVwqs iTunes: https://podcasts.apple.com/ca/podcast/better-left-unsaid-with-curt-jaimungal/id1521758802 Pandora: https://pdora.co/33b9lfP Spotify: https://open.spotify.com/show/4gL14b92xAErofYQA7bU4e Subreddit r/TheoriesOfEverything: https://reddit.com/r/theoriesofeverything TIMESTAMPS: 00:00:00 Introduction 00:03:35 An overview of Michael's results of code that isn't genomic 00:07:08 What's the standard view in development biology? (compare and contrast) 00:08:30 Regenerating limbs on animals which don't have regenerative properties (watch this first) 00:17:01 Why did it take so long to discover this momentous result? 00:20:42 Precisely what is voltage and what's being visualized? 00:23:23 DNA encodes hardware, and Michael discovered the software 00:27:22 Taking a cancerous cell and making it non-cancerous, and vice versa 00:32:23 What is the Self? (on identity and ego) 00:33:55 Living robots (xenobots) 00:44:50 The terms "alive" and "dead" are almost useless now 00:47:15 Perception and the morphogenetic code 00:51:06 Immortality is possible in flatworms... What about humans? 00:52:18 Jungian archetypes and their relation to the morphogenetic code 00:54:38 Curt believes this is Nobel prize winning work 00:55:53 [Rupert Sheldrake] Morphogenetic fields vs code 00:57:05 Engineering xenobots to clean up the environment 00:58:17 5G and its possible effects? 01:00:32 Microbiome and the non-neural electric imprints 01:02:34 How do you decode the code? What factors go are in play? 01:05:57 Psychedelics ⇒ change in morphogenetics? 01:07:13 The least action principle, intelligence, and the "intention" of particles 01:16:18 Studying consciousness is a first person activity, not a third person 01:18:13 [Faraz Honarvar] Does the code differ between people? 01:19:48 Morphoceuticals 01:22:03 [Nadia Markova] How does the ML algorithm work, specifically? 01:23:46 [Sam Thompson] Biological self-emergence is "proto-algorithmic"? 01:28:36 [Thane] Should we regenerate? Isn't it beneficial to NOT regenerate? 01:31:23 [Tom] Penrose's and Hameroff's Orch OR 01:35:59 [Mo Flow] Biological clock, aging, and David Sinclair 01:38:29 [Nate Grundmann] Placebo, healing yourself with your mind, and Joe Dispenza 01:44:53 Future projects of Prof. Michael Levin 01:46:01 Consciousness and developmental biology are related * * * Just wrapped (April 2021) a documentary called Better Left Unsaid http://betterleftunsaidfilm.com on the topic of "when does the left go too far?" Visit that site if you'd like to watch it. Learn more about your ad choices. Visit megaphone.fm/adchoices
AI Today Podcast: Artificial Intelligence Insights, Experts, and Opinion
This podcast episode provides a snippet of Cognilytica's AI and ML education from our Cognilytica Education Subscription. Data is at the heart of AI. It should be no surprise then that proper data management is crucial for AI projects. This podcast is an excerpt from our Cognilytica Education course “Managing Data for AI”. In this clip we discuss the history of how we stored data in the past and moving from transactional systems to analytics systems. Continue reading AI Today Podcast: AI Education Series: Managing Data for AI at Cognilytica.
Can we live with openSUSE Tumbleweed? We try three different builds and prepare ourselves for our journey into SUSE land. Our setups, what we liked, and what we still need to figure out.
We’re learning all about Vertex AI this week as Carter Morgan and Jay Jenkins host guest Erwin Huizenga. He helps us understand what is meant by Asia Pacific and how Machine Learning is growing there. APAC’s Machine Learning scene is exciting for its enterprise companies leveraging ML for innovative projects at scale. The ML journey of many of these customers revealed challenges with things like efficiency that Vertex AI was built to solve. The Vertex AI platform boasts tools that help with everything from the beginning stages of data collection to analysis, validation, transformation, model training, evaluation, serving the model, and metadata tracking. Erwin offers detailed examples of this pipeline process and describes how Feature Store helps clients manage their projects. Using Vertex AI not only simplifies the initial development process but streamlines the iteration process as the model is adjusted over time. Pipelines offers automation options that help with this, Erwin explains. ML Operations are also built into Vertex AI to ensure everything is done in compliance with industry standards, even at scale. Using customer recommendations as an example, Erwin walks us through how Vertex AI can employ embedding to enhance customer experiences through ML. By using Vertex AI in combination with other Google offerings like AutoML, companies can effectively build working ML projects without data science experience. We talk about the Vertex AI user interface and the other tools and APIS that are available there. Erwin tells us how Digits Financial uses Vertex AI and Pipeline to bring models to production in days rather than months, and how others can get started with Vertex AI, too. Erwin Huizenga Erwin Huizenga is a Data Scientist at Google specializing in TensorFLow, Python, and ML. Cool things of the week Announcing Spot Pods for GKE Autopilot—save on fault tolerant workloads blog Indosat Ooredoo and Google Launch Strategic Partnership to Accelerate Digitalization Across SMBs and Enterprises in Indonesia site Indosat Ooredoo dan Google Luncurkan Kemitraan Strategis untuk Percepatan Digitalisasi UMKM dan Perusahaan di Indonesia site Interview Vertex AI site Google Cloud in Asia Pacific blog Introduction to Vertex AI docs What Is a Machine Learning Pipeline? site TensorFlow site PyTorch site Vertex AI Feature Store docs AutoML site BigQuery ML site Vertex AI Matching Engine docs ScaNN site Announcing ScaNN: Efficient Vector Similarity Search blog Vertex AI Workbench site Vertex Pipeline Case Study: Digits Financial site Intro to Vertex Pipelines Codelab site Vertex AI: Training and serving a custom model Codelab site Vertex AI Workbench: Build an image classification model with transfer learning and the notebook executor Codelab site APAC Best of Next 2021 site TFX: A TensorFlow-Based Production-Scale Machine Learning Platform site Rules of Machine Learning site Google Cloud Skills Boost: Build and Deploy Machine Learning Solutions on Vertex AI site Monitoring feature attributions: How Google saved one of the largest ML services in trouble blog What’s something cool you’re working on? Jay is working on APAC Best of Next and will be doing a session on sustainability! Carter is working on transitioning the GCP Podcast to a video format!
Grape consumption benefits gut microbiome and cholesterol metabolism University of California at Los Angeles, November 11, 2021 A new clinical study published in the scientific journal Nutrients found that consuming grapes significantly increased the diversity of bacteria in the gut which is considered essential to good health overall. Additionally, consuming grapes significantly decreased cholesterol levels, as well as bile acids which play an integral role in cholesterol metabolism. The findings suggest a promising new role for grapes in gut health and reinforce the benefits of grapes on heart health. In the intervention study], healthy subjects consumed the equivalent of 1.5 cups of grapes[2] per day – for four weeks. The subjects consumed a low fiber/low polyphenol diet throughout the study. After four weeks of grape consumption there was an increase in microbial diversity as measured by the Shannon index, a commonly used tool for measuring diversity of species. Among the beneficial bacteria that increased was Akkermansia, a bacteria of keen interest for its beneficial effect on glucose and lipid metabolism, as well as on the integrity of the intestinal lining. Additionally, a decrease in blood cholesterols was observed including total cholesterol by 6.1% and LDL cholesterol by 5.9%. Bile acids, which are linked to cholesterol metabolism, were decreased by 40.9%. Vitamin D supplementation associated with lower risk of heart attack or death during follow-up Kansas City VA Medical Center, November 8 2021. The October 2021 issue of the Journal of the Endocrine Society published findings from a retrospective study of US veterans that uncovered an association between supplementing with vitamin D and a lower risk of heart attack and mortality from any cause during up to 14 years of follow-up. The study included men and women treated at the Kansas City VA Medical Center from 1999-2018 who had low 25-hydroxyvitamin D levels of 20 ng/mL or less. Among 11,119 patients who were not treated with vitamin D supplements, follow-up vitamin D levels remained at 20 ng/mL or lower. For those who received the vitamin, levels improved to 21-29 ng/mL among 5,623 patients and to at least 30 ng/mL among 3,277 patients at follow-up. Men and women whose vitamin D levels improved to at least 30 ng/mL had a risk of heart attack that was 35% lower than patients whose levels improved to 21-29 ng/mL and 27% lower than the untreated group. The difference in risk between untreated individuals and those whose levels improved to 21-29 ng/mL was not determined to be significant. Patients whose vitamin D levels improved the most also experienced significantly greater heart attack-free survival during follow-up than the remainder of the patients. When mortality from any cause during follow-up was examined, men and women whose vitamin D levels improved to 21-29 ng/mL had a 41% lower risk, and those whose levels improved to 30 ng/mL or more had a 39% lower risk than the untreated group. “These results suggest that targeting 25-hydroxyvitamin D levels above 30 ng/mL might improve prognosis in the primary prevention setting among individuals with vitamin D deficiency,” authors Prakash Acharya of the University of Kansas Medical Center and colleagues wrote. Meditative practice and spiritual wellbeing may preserve cognitive function in aging Alzheimer's Research and Prevention Foundation and Thomas Jefferson University, November 12, 2021 It is projected that up to 152 million people worldwide will be living with Alzheimer's disease (AD) by 2050. To date there are no drugs that have a substantial positive impact on either the prevention or reversal of cognitive decline. A growing body of evidence finds that targeting lifestyle and vascular risk factors have a beneficial effect on overall cognitive performance. A new review in the Journal of Alzheimer's Disease, published by IOS Press, examines research that finds spiritual fitness, a new concept in medicine that centers on psychological and spiritual wellbeing may reduce multiple risk factors for AD. Research reveals that religious and spiritual involvement can preserve cognitive function as we age. Significantly, individuals who have a high score on a "purpose in life" (PIL) measure, a component of psychological wellbeing, were 2.4 times more likely to remain free of AD than individuals with low PIL. In another study, participants who reported higher levels of PIL exhibited better cognitive function, and further, PIL protected those with already existing pathological conditions, thus slowing their decline. Radiotherapy may explain why childhood cancer survivors often develop metabolic disease Rockefeller University, November 9, 2021 Decades after battling childhood cancer, survivors often face a new challenge: cardiometabolic disease. A spectrum of conditions that includes coronary heart disease and diabetes, cardiometabolic disease typically impacts people who are obese, elderly, or insulin resistant. For reasons yet unknown, young, seemingly healthy adults who survived childhood cancer are also at risk. Radiation therapy may be to blame. A new study finds that childhood cancer patients who were treated with abdominal or total body irradiation grow up to display abnormalities in their adipose (fat) tissue, similar to those found in obese individuals with cardiometabolic disease. "When physicians are planning radiation therapy, they are very conscious of toxicity to major organs. But fat is often not considered," says Rockefeller's Paul Cohen. "Our results imply that the early exposure of fat cells to radiation may cause long-term dysfunction in the adipose tissue that puts childhood cancer survivors at higher risk of cardiometabolic disease." Researchers discover link between dietary fat (palm oil) and the spread of cancer Barcelona Institute of Science and Technology (Spain), November 10, 2021 The study, published in the journal Nature and part-funded by the UK charity Worldwide Cancer Research, uncovers how palmitic acid alters the cancer genome, increasing the likelihood the cancer will spread. The researchers have started developing therapies that interrupt this process and say a clinical trial could start in the next couple of years. Newly published findings reveal that one such fatty acid commonly found in palm oil, called palmitic acid, promotes metastasis in oral carcinomas and melanoma skin cancer in mice. Other fatty acids called oleic acid and linoleic acid—omega-9 and omega-6 fats found in foods such as olive oil and flaxseeds—did not show the same effect. Neither of the fatty acids tested increased the risk of developing cancer in the first place. The research found that when palmitic acid was supplemented into the diet of mice, it not only contributed to metastasis, but also exerts long-term effects on the genome. Cancer cells that had only been exposed to palmitic acid in the diet for a short period of time remained highly metastatic even when the palmitic acid had been removed from the diet. The researchers discovered that this "memory" is caused by epigenetic changes—changes to how our genes function. The epigenetic changes alter the function of metastatic cancer cells and allow them to form a neural network around the tumor to communicate with cells in their immediate environment and to spread more easily. By understanding the nature of this communication, the researchers uncovered a way to block it and are now in the process of planning a clinical trial to stop metastasis in different types of cancer. Study finds consuming nuts strengthens brainwave function Loma Linda University, November 15, 2021 A new study has found that eating nuts on a regular basis strengthens brainwave frequencies associated with cognition, healing, learning, memory and other key brain functions. In the study titled "Nuts and brain: Effects of eating nuts on changing electroencephalograph brainwaves," researchers found that some nuts stimulated some brain frequencies more than others. Pistachios, for instance, produced the greatest gamma wave response, which is critical for enhancing cognitive processing, information retention, learning, perception and rapid eye movement during sleep. Peanuts, which are actually legumes, but were still part of the study, produced the highest delta response, which is associated with healthy immunity, natural healing, and deep sleep. The study's principal investigator, Lee Berk, DrPH, MPH, associate dean for research at the LLU School of Allied Health Professions, said that while researchers found variances between the six nut varieties tested (almonds, cashews, peanuts, pecans, pistachios and walnuts), all of them were high in beneficial antioxidants, with walnuts containing the highest antioxidant concentrations of all. Why Nitrates And Nitrites In Processed Meats Are Harmful – But Those In Vegetables Aren't University of Hertfordshire (UK), November 11, 2021 While there are many reasons processed meats aren't great for our health, one reason is because they contain chemicals called nitrates and nitrites. But processed meats aren't the only foods that contain these chemicals. In fact, many vegetables also contain high amounts – mainly nitrates. And yet research suggests that eating vegetables lowers – not raises – cancer risk. So how can nitrates and nitrites be harmful when added to meat but healthy in vegetables? The answer lies in how nitrates and nitrites in food get converted into other molecules. Nitrates and nitrites occur attached to sodium or potassium, and belong to a family of chemically related molecules that also includes the gas nitric oxide. Vegetables such as beetroot, spinach and cabbages are particularly good sources of nitrates. When we eat something containing nitrates or nitrites, they may convert into a related molecular form. For example, nitrate in vegetables and in the pharmaceutical form nitroglycerine (which is used to treat angina), can convert in the body into nitric oxide. Nitric oxide dilates blood vessels, which can reduce blood pressure. It's actually sodium nitrite – not nitrate – that's linked to cancer. But if consuming nitrites alone directly caused cancer, then even eating vegetables would be harmful to us. Given this isn't the case, it shows us that cancer risk likely comes from when the sodium nitrites react with other molecules in the body. So it isn't necessarily the nitrates and nitrites themselves that cause health issues – including cancer. Rather, it's what form they are converted into that can increase risk – and what these converted molecules interact with in our bodies. The main concern is when sodium nitrite reacts with degraded bits of amino acids – protein fragments our body produces during the digestion of proteins – forming molecules called N-nitroso compounds (NOCs). These NOCs have been shown to cause cancer. Obama Climate & Environment Record Seasoned environmentalists were very skeptical of obama from the very start n the 2008 campaign -- notably his coal to liquid technology he advocated and his great enthusiasm for ethanol Sold off 2.2 billion tons of coal from public land (Greenpeace report). The sales to private interests generated $2.3 billon but CO2 damage estimated between $52-530 billion His Clean Power Plan -- which Trump administration later trashed -- really had little to do with the plan's name -- had nothing to do with eradicating hazardous pollutants from power generation; it was primarily all based on a cap and trade system to regulate carbon dioxide Ran on campaign that by 2025, 25% of US energy would be renewable Was never anywhere close on being on track for that goal Promoted fracking as a move away from coal to natural gas -- this was a midst promises to have highest standards for fracking on federal land -- never happened Lowered natural gas export restrictions in order to sell more US natural gas to foeign customers Made efforts to weaken rules.on methane leaks from oil and gas operations -- leaks account or 3 percent of US gas emissions Also instrumental in pushing on behalf of pipeline companies and terminals to have major coastal terminals for gas exports (most notable example was Cove Point terminal in Maryland that Obama touted Flint Water crisis Sued the EPA over a dozen ties against the agency's effort to increase environmental regulations on corporations Opened more federal and land (18% increase between 2009-2014) for oil and gas drilling -- including "off limits" regions in the mid Atlantic coast, along Alaska's Arctic coast and Gulf of mexico, Completely failed on setting rules or clean disposal of coal ash byproduct -- US produces about 100 million tons of this crap annually and just dumps into holes in the ground Went soft on ozone pollution and smog rules -- did lower Bush's ozone threshold from 75ppb to 70 ppb, but his EPA was recommending 60-65 ppb Very insensitive to wood pellet development under the disguise as a renewable -- part of his clean power plan
One of the world's biggest defense contractors, BAE Systems, has to navigate the world of cloud computing just like everyone else. But the stakes are much higher. The company not only provides weapons systems to the U.S. military but cybersecurity protecting highly classified intelligence. In this podcast segment, Dr. Nandish Mattikalli, the chief engineer for […]
TLP079 is brought to you by T78! a.k.a Manuele Tessarollo is an Italian producer with an intensive background in the music industry. This can be heard by his unique approach to Techno, combined with outstanding production quality and his energetic on stage performances, which made him rise rapidly into the scene.In January 2020, T78 had 10 tracks flying around in the Beatport Techno top 100, claiming the #1 spot with ‘Hardcore' which was released on Filth on Acid. This wasn't an exception as the entire 2019 his releases had high entries in the techno charts, staying and re-entering regularly, which made him overall #5(2019) and #4 (2020) of bestselling Techno artist for Beatport.His singles aren't just being supported by DJ's like Carl Cox, Pan Pot, Ritchie Hawtin, Amelie Lens and many more, millions of fans around the world like to stream his music too! With average listeners of 700.000+ each month on Spotify, in just 5 years, T78 has already produced some true techno classics like “The Antidote”(3 ML), ‘Megator'(6+ML), ‘Acid Lick' (3,5ML) or his remix for Christian Cambas ‘The Outsiders'(8+ML). His skills are not limited to producing. He is also a highly skilled DJ, his sets are always an exciting spectacle as he perfectly connects with the crowd while delivering his own productions. T78 is a perfect example how to create an amazing vibe for a good "mood party".T78 has raised the bar yet again for 2020 with his own label Autektone. In just three years the label managed to be #8 best selling Techno Label at Beatport. He wants to take a new yet revived approach to electronic dance music as a DJ and producer. He recently quoted “We receive so many outstanding productions each day, that me and the Autektone Team decided to do more releases, with quality Techno music from the respected names and new kids pulling the wagon for a new generation! I want to create a label that embraces the spirit of electronic dance music from the late 90's. An era in which music wasn't pigeon-holed constantly and DJ's were versatile and eclectic. And so far we did goooooood!” In 2020 Autektone provided you with even more outstanding releases by: A*S*Y*S, ROBPM, Space92, Nusha, Raito, Fatima Hajji and more exciting, promising and established names in the world of Techno…For those who want to keep up to date about which's tracks are doing it for T78 check out his monthly podcast; -onlybombs- Tune in and find out which bomb is ticking in the mind of T78.
This Week in Machine Learning & Artificial Intelligence (AI) Podcast
Today we're joined by David Ha, a research scientist at Google. In nature, there are many examples of “bottlenecks”, or constraints, that have shaped our development as a species. Building upon this idea, David posits that these same evolutionary bottlenecks could work when training neural network models as well. In our conversation with David, we cover a TON of ground, including the aforementioned biological inspiration for his work, then digging deeper into the different types of constraints he's applied to ML systems. We explore abstract generative models and how advanced training agents inside of generative models has become, and quite a few papers including Neuroevolution of self-interpretable agents, World Models and Attention for Reinforcement Learning, and The Sensory Neuron as a Transformer: Permutation-Invariant Neural Networks for Reinforcement Learning. This interview is Nerd Alert certified, so get your notes ready! PS. David is one of our favorite follows on Twitter (@hardmaru), so check him out and share your thoughts on this interview and his work! The complete show notes for this episode can be found at twimlai.com/go/535
There is always a little magic behind every great design. On this episode of the Design Mind frogcast, we're joined by Dave Lankford, VP of Product for Global Consumer Engagement at Disney Streaming (Disney+, Hulu, ESPN+ and Star+) to talk about what it means to design products that tell stories. Designing streaming platforms for a brand with as large a footprint as Disney is no small feat, but luckily Dave and his global team are well-prepared for the task. At Disney Streaming, human empathy and machine intelligence play a critical role in the mission of storytelling. Dave discusses the importance of empowering creative, collaborative teams, how the improvisation technique “Yes, and” leads to innovative ideas, and what it takes to connect users with stories across vastly different regions, cultures and languages.Brought to you by frog, a global creative consultancy. frog is part of Capgemini Invent. (https://www.frogdesign.com)Find episode transcripts and relevant info (https://www.frogdesign.com/designmind/design-mind-frogcast-ep-17-the-magic-of-storytelling/)Download the frog report 'Convergent Transformation' (https://www.frogdesign.com/designmind/real-transformation-and-disruption-takes-convergent-design)Audio Production: Richard Canham, Lizard Media (https://www.lizardmedia.co.uk/)
Matthew Coatney, CIO at Thompson Hine, and author of The Human Cloud sits down and talks about what he sees as the transformation of how we work. According to Coatney, freelancing and project-based work (The Human Cloud) combined with Artificial Intelligence and Machine Learning (The Machine Cloud) will soon disrupt the way we deliver work. Law firms will not be exempt from this disruption. Matters are really just projects. Contract attorneys are freelancers. According to some experts, 80% of work to be done by organizations in the 2030s will be project-based work. And AI and ML will eat into the other 20%. Coatney says that we are missing out on an opportunity if we are not preparing for this reality. We asked how life as a CIO has changed over the past couple of decades for a CIO in a law firm and Coatney says that a CIO of 2000 would have culture shock if they were to be transported to today. CIOs are still the brand ambassadors of the IT departments, but Chief Technology Officers and Chief Data Officers are making their way into the fold to help offload some of the overwhelming responsibility that many of today's CIOs find falls on their shoulders. Matt also co-hosts The Human Cloud Podcast with Matthew Mottola where they put out twice-weekly episodes diving deeper into these topics. Go check out "The Matthews" on their own pod if you're curious about how the structure of work is going to change. Information Inspirations You may have noticed that we took last week off from this podcast, but we were busy recording other podcasts to fill the void. Greg went on the Legal Value Network's "Off the Clock" podcast and talked with Keith Maziarek of Katten and Percipent's Chad Main about the recent increase of available APIs from a number of legal information vendors. These APIs may very well open the door to a much easier method of pulling data in from vendors directly into internal law firm databases to better prepare firms to handle clients' needs. Marlene hosted an ILTA podcast panel on How Virtual Hearings Altered the Fabric of Dispute Resolution with Florida Circuit Judge Christopher Sprysenski, Trial Consultant with Paul Hastings, Jeremy Cooper, and Jackson Walker Partner, Richard Howell. The three give their personal experiences on how they handled virtual trials over the past twenty months. Contact Us Twitter: @gebauerm or @glambert. Voicemail: 713-487-7270 Email: geekinreviewpodcast@gmail.com. Music: As always, the great music you hear on the podcast is from Jerry David DeCicca. Transcripts available on 3 Geeks and a Law Blog.
AI Today Podcast: Artificial Intelligence Insights, Experts, and Opinion
The saying garbage in is garbage out couldn't be more true when it comes to data being fed into AI and ML models. In this podcast, hosts Kathleen Walch and Ron Schmelzer discuss the importance of data quality and why bad data is a main reason for AI project failure. Show Notes: CPMAI Methodology CPMAI MethodologyIntro to CPMAI webinar AI Today Podcast: AI Failure Series – Data Quantity & Data Understanding Issues AI Today Podcast: AI Failure Series – ROI Misalignment Continue reading AI Today Podcast: AI Failure Series- Data Quality Issues at Cognilytica.
ML's city council campaign is over, so let the post mortem begin! Shawn fawns, but a fight breaks out nevertheless. […]
It's never too early to build your data infrastructure. You can always start small and scale it. Today, I welcome back Govind Balu, Founder of QuaXigma, to chat about the power in the strategic value of data analytics, and ultimately machine learning and artificial intelligence. Govind and I dive into ways on how to set up a business for a smooth sailing data & analytics system. Govind also shares how his firm helps businesses accelerate their digital transformation by creating customer-centric solutions. You'll surely come out of this episode with the perfect idea on how you'll do data analytics for your business so tune in now! We'll talk about: Introduction [00:00] Data challenges that Govind see in SMEs [04:11] Govind's data organization tip for small companies [6:21] Having the right data on making business decisions [11:47] Keeping your database clean starting from the early days [14:02] Including data strategies to customer journey roadmap [18:10] Enabling your eCommerce strategy with data, AI, and ML [22:19] Considerations to take note of for a better customer experience [26:20] Govind's piece of advice for startups [31:16] Developing data strategies doesn't have to be complicated [34:33] Professional recommendations from Govind [36:22] Resource Links: Brett Trainor Website (https://bretttrainor.com/) Download Startup to Scaleup: A 4-Part Framework to Grow Your B2B Business to $10 Million (https://bretttrainor.com/resources/) Qua Xigma website (http://www.quaxigma.com/) Tune in to Episode 42 with Govind Balu at (https://hardwiredforgrowth.libsyn.com/42-why-data-analytics-could-be-the-difference-between-success-and-failure-for-your-startup) About Our Guest: Govind Balu is the Founder and CEO of QuaXigma, a Data Analytics firm that aims to create customer-centric solutions that accelerate digital business transformation and unleash actual value by re-engineering the power of data and AI. Govind has worked in the data and analytics industry for nearly three decades. Prior to founding his own company, he worked as a lead data scientist for companies including Bank of America and Allstate. Connect with Govind Balu: LinkedIn: https://www.linkedin.com/in/govindbalu/ https://www.linkedin.com/company/quaxigma/ Website: http://www.quaxigma.com/contact.html Connect with me and learn more about growing your business: Email: BT@BrettTrainor.com LinkedIn: https://www.linkedin.com/in/bretttrainor/ YouTube: https://www.youtube.com/channel/UCySoKsETeKxu-Fnf2VfE7Gg Facebook: https://www.facebook.com/TrainorBrett Twitter: https://twitter.com/Brett_Trainor Instagram: https://www.instagram.com/bretttrainor/ If you liked this episode, please don't forget to tune in, subscribe, and share this podcast.
Davit is the founding CEO of Activeloop.ai (Database for AI), They are a Y Combinator company. 90% of the data in the world that is generated is unstructured form like images, videos, etc… Activeloop helps businesses make sense of this data.You can say that Activeloop is an autodata company. They connect raw data to machine learning models, instantly. They empower data scientists to focus on training ML models, instead of messing with the data. Acitiveloop enables organizations to unlock the true potential of the unstructured data, faster and cheaper.It is backed by Y Combinator, Tribe Capital, SmartGate, and other prominent angels in Silicon Valley.In this podcast episode we talk about building startups. Artificial Intelligence, Machine learning and Blockchain, Crypto and much more...Book recommendationRay Dalio - PrinciplesConnect with Davit:-https://www.linkedin.com/in/davidbuniatyan/https://www.activeloop.ai/If you enjoyed this episode then please subscribe, I will be interviewing other successful founders and investors to provide you a shortcut to success.Follow instagram:- https://www.instagram.com/wantmoneygotmoney/
Welcome to this special podcast series, Series Spotlight: Revolutionizing GRC with 6clicks, sponsored by 6clicks. This week I visit with Joe Schorr, Vice President (VP) of Global Channel Sales, Andrew Robinson, co-founder and Chief Information Security Officer, Stephen Walter, head of Marketing, Dr. Heather Buker, Chief Technology Officer, and Ant Stephens, co-founder and Chief Executive Officer. Over the series, we will break down 6ckicks Hub and Spoke approach, utilizing Artificial Intelligence (AI) and Machine Learning (ML) in governance, risk and compliance (GRC), curating and maintaining a robust GRC content, producing audit ready reports, and look at what's next for 6clicks down the road. In Part 2, I am joined by Andrew Robinson to discuss utilizing ML and AI into your GRC practice. For GRC professionals working internationally, Robinson said they must “maintain mappings or what you commonly call in the US ‘crosswalks of compliance' frameworks.” He went on to explain these frameworks are “useful because it can allow a consultant to help a client understand how they might stack up against a particular standard. Robinson provided the example that if an organization is already complying with ISO 27,001, through these mappings, it might be able to give them an idea about what that level of compliance they have through the lens of a different framework or standard that may be relevant like the NIST cybersecurity framework.” This productivity increase and potential cost saving does not remove the human element. This final concept is critical in moving forward. Robinson said, “I'm of the view that humans have a very important role to play. This role is supervising the machine learning models to make sure that what they are producing and the results that they are coming out with are accurate and reliable.” If they are using spreadsheets and word documents; they should, come to terms with the fact that companies and clients no longer want spreadsheets and word documents as a deliverable. GRC professionals and consultants need to need to start using similar tools and improving the way that they service their clients. Clients, both in-house and external, are starting to demand and look for this approach. Robinson noted, “the reality is that if you are doing anything else it will be seen as subpar, and no one wants to be delivering sort of subpar products. I look for a solution that can meet your customer expectations and help you deliver your services long into the future.” We concluded by looking at GRC tools with ML and AI at a strategic level, at the senior executive level and even at the Board of Director level. Robinson feels that management at this level “understands the benefits because they understand the problem.” Their goals are to simplify compliance while understanding risk exposure. From this point, management can move to create a risk-based solution. Robinson believes, these are the types of “business problems that executives are dealing with on a daily basis. Having awareness of the machine learning model can help them navigate that complexity.” From where I sit, when you can take a tool that improves business process efficiency and use it to increase profitability through more effectual risk management it is a win for everyone. Join us tomorrow where we take up the topic of curating and maintaining robust GRC content. With 6clicks Head of Marketing, Stephen Walter. For more information on 6clicks, check out their website here.
Wayne Haber, is the Director of Engineering at GitLab. Gitlab is a complete DevOps platform, to help teams improve development cycle time from weeks to minutes. Wayne is also a veteran of three successful startups (including GitLab) and has experience in multiple areas including healthcare, finance, and security. Wayne talks about how bringing transparency and constantly iterating leads to growth and fulfillment. He is excited about applying ML to improve user experience and loves the environment of continuous collaboration at Gitlab.
Many of us have probably caught ourselves talking to the computer; perhaps, sometimes, even yelling at it. Now the computer can talk back. At first, that may seem daunting or even worrisome. But overall, it's a good thing because it's going to make our lives easier. Conversational A.I. has made great strides over the last ten years. As proof, look no further than the applications in commerce where many companies are already using chatbots. Despite these advancements, though, there's still a long way to go to really get computers and people communicating effectively. On this episode of Future of Tech, Joe Bradley, Chief Scientist at LivePerson, discusses the current state of conversational A.I., where the technology is heading, and the steps that need to be taken to get there. Joe explains how advances are being made in A.I. understanding language as well as in dialogue management. He also shares how there's a lot of work to be done on the goal-oriented dialogue side of the technology and making sure bias is checked as systems are built. So what's the future of computers and people communicating? Find out on this episode! Main Takeaways: Conversational A.I. Right Now: Conversational A.I. involves both understanding natural language and dialogue management. In terms of A.I., or machine learning, understanding language has come very far. Developing dialogue that supports effective communication between computers and people still has a ways to go. The Future of Conversational A.I.: Conversational A.I. has to improve between computers and people. The computer, of course, needs to get better at understanding complex aspects of human language. It also needs to be able to learn if its dialogue is achieving the desired goal. The other component to good communication is that people need to be educated on how to speak to computers. Language at Play: In our digital world, language is still very important. Perhaps it's more important than ever to communicate effectively because of all available information at our fingertips. We don't need to fear emojis taking over language. They are shorthand symbols that can augment language. Language evolves, and that's how it's supposed to be. Being Well-Rounded Pays Off: Being someone who is very specific and focused comes with creating technology. But having diverse interests is only an asset. Passion in areas outside a person's primary work demonstrates a mental fluidity and a posture of openness. --- Future of Tech is brought to you by Amdocs Tech. Amdocs Tech is Amdocs's R&D and technology center, paving the way to a better-connected future by creating open, innovative, best-in-class products and continuously evolving the way we work, learn and live. To learn more about Amdocs Tech, visit the Amdocs Technology page on LinkedIn.
Technology has already come after several blue collar jobs of the past, like assembly line workers, cashiers, phone operators, and travel agents, to name a few.But is it possible for AI to automate and replace the job of a software engineer? Most technology we use today involves software - from watching our favorite shows on Netflix, to ordering a Starbucks pickup, to scheduling an early morning Uber to the airport. It should come as no surprise that programming has been the most in-demand job in our digital economy over the past 20 years. But as of late, a fascinating new technology known as GitHub Pilot has been making waves in tech. Copilot is an automatic coding tool, powered by OpenAI, one of the worlds leading AI research laboratories and founded by tech titans such as Elon Musk and Sam Altman. It can effectively look at code written by a human programmer and suggest further lines or alternative code, eliminating some of the repetitive labor that goes into software development. Today, we chat with Nick Vincent once again, but this time about the ethics and irony of AI being able to automate programming itself.Follow us on Instagram, Facebook, Twitter, and LinkedIn to keep up with the latest stories in our ever-changing digital economy. @thingshavechangedpodSupport the show (https://www.thc-pod.com/)
The Prop King gives us peasants all of his favorite prop plays for the NFL Week 9 slate. Ken Barkley tries to hit his second straight ML underdog parlay. Learn more about your ad choices. Visit podcastchoices.com/adchoices
In today's bonus episode, host Mark Graban talks about an error that he was "victim" of this week. He was given the incorrect Moderna booster dose, being given the "full" 0.5 mL dose instead of the "booster" dose of 0.25 mL. This is, thankfully, an error that's not harmful (in fact, it may be to his benefit). But, everyone, from the CDC to the store, pharmacy manager agreed this was a "serious" error that "should not occur." How can we learn from mistakes like this so we prevent giving the wrong dose (or the wrong vaccine)?? Will learning from this help prevent future errors that might be more serious? You can read more in a blog post that Mark about this. --- Support this podcast: https://anchor.fm/favorite-mistake/support
And they're off! In this week's episode of The Pony Pundits: Marco, Sig and Sean preview Saturday's Breeders' Cup Classic from Del Mar. Knicks Go has opened as the 5-to-2 morning line favorite after winning seven of his last nine races. Join Marco, Sig and Sean as they preview the field and share their top picks for horse racing's annual showcase from Del Mar.#HorseRacing | #BreedersCup | #DelMar1) Tripoli (15-1 ML)2) Express Train (20-1 ML)3) Hot Rod Charlie (4-1 ML)4) Essential Quality (3-1 ML)5) Knicks Go (5-2 ML)6) Art Collector (8-1 ML)7) Stiletto Boy (30-1 ML)8) Medina Spirit (4-1 ML)9) Max Player (8-1 ML)00:00 Introduction05:00 Entry Breakdowns19:45 Show Selections
Part 2 of deploying your ML models to the cloud with SageMaker (MLOps) MLOps is deploying your ML models to the cloud. See MadeWithML for an overview of tooling (also generally a great ML educational run-down.) SageMaker Jumpstart Deploy Pipelines Monitor Kubernetes Neo
On The Cloud Pod this week, half the team misses Rob and Ben. Also, AWS Gaudi Accelerators speed up deep learning, GCP announces that its Tau VMs are an independently verified delight, and Azure gets the chance to be Number One for once (with industrial IoT platforms.) A big thanks to this week's sponsors: Foghorn Consulting, which provides full-stack cloud solutions with a focus on strategy, planning and execution for enterprises seeking to take advantage of the transformative capabilities of AWS, Google Cloud and Azure. JumpCloud, which offers a complete platform for identity, access, and device management — no matter where your users and devices are located. This week's highlights
This Week in Machine Learning & Artificial Intelligence (AI) Podcast
Today we're joined by Francesc Joan Riera, an applied machine learning engineer at The LEGO Group. In our conversation, we explore the ML infrastructure at LEGO, specifically around two use cases, content moderation and user engagement. While content moderation is not a new or novel task, but because their apps and products are marketed towards children, their need for heightened levels of moderation makes it very interesting. We discuss if the moderation system is built specifically to weed out bad actors or passive behaviors if their system has a human-in-the-loop component, why they built a feature store as opposed to a traditional database, and challenges they faced along that journey. We also talk through the range of skill sets on their team, the use of MLflow for experimentation, the adoption of AWS for serverless, and so much more! The complete show notes for this episode can be found at twimlai.com/go/534.
BLACKGAZE IS BACK! MØL have grabbed the torch that Deafheaven dropped and ran all the way home with it. Seeyouspacecowboy evolve once more and Portrayal Of Guilt prove they are one of the most interesting and vital bands in extreme music. Thanks for listening homies much love!
Watch the live stream: Watch on YouTube About the show Sponsored by Shortcut Special guest: Morleh So-kargbo Michael #1: Django 4.0 beta 1 released Django 4.0 beta 1 is now available. Django 4.0 has an abundance of new features The new *expressions positional argument of UniqueConstraint() enables creating functional unique constraints on expressions and database functions. The new scrypt password hasher is more secure and recommended over PBKDF2. The new django.core.cache.backends.redis.RedisCache cache backend provides built-in support for caching with Redis. To enhance customization of Forms, Formsets, and ErrorList they are now rendered using the template engine. Brian #2: py - The Python launcher py has been bundled with Python for Windows only since Python 3.3, as py.exe See Python Launcher for Windows I've mostly ignored it since I use Python on Windows, MacOS, and Linux and don't want to have different workflows on different systems. But now Brett Cannon has developed python-launcher which brings py to MacOS and various other Unix-y systems or any OS which supports Rust. Now py is everywhere I need it to be, and I've switched my workflow to use it. Usage py : Run the latest Python version on your system py -3 : Run the latest Python 3 version py -3.9 : Run latest 3.9 version py -2.7 : Even run 2.x versions py --``list : list all versions (with py-launcher, it also lists paths) py --``list-paths : py.exe only - list all versions with path Why is this cool? - I never have to care where Python is installed or where it is in my search path. - I can always run any version of Python installed without setting up symbolic links. - Same workflow works on Windows, MacOS, and Linux Old workfow Make sure latest Python is found first in search path, then call python3 -m venv venv For a specific version, make sure python3.8, for example, or python38 or something is in my Path. If not, create it somewhere. New workflow. py -m venv venv - Create a virtual environment with the latest Python installed. After activation, everything happens in the virtual env. Create a specific venv to test something on an older version: py -3.8 venv venv --``prompt '``3.8``' Or even just run a script with an old version py -3.8 script_name.py Of course, you can run it with the latest version also py script_name.py Note: if you use py within a virtual environment, the default version is the one from the virtual env, not the latest. Morleh #3: Transformers As General-Purpose Architecture The Attention Is All You Need paper first proposed Transformers in June 2017. The Hugging Face (
Show notes Part 1 of deploying your ML models to the cloud with SageMaker (MLOps) MLOps is deploying your ML models to the cloud. See MadeWithML for an overview of tooling (also generally a great ML educational run-down.) SageMaker DataWrangler Feature Store Ground Truth Clarify Studio AutoPilot Debugger Distributed Training And I forgot to mention JumpStart, I'll mention next time.
Drew gets support in his CVS battle, Halloween recap, ML Elrick checks in on election eve, Sleepy Joe justified for sleeping, Gen Z's making Millennial bosses nervous, Stan Edwards v. 97.1, and Eli stops by to see it his way.World Series: The Houston Astros take Game 5 of the World Series despite the Atlanta Braves hitting a grand slam. The last time that happened someone's best friend was playing in the game. The Astros seem to hate Justin Verlander. Miggy wants JV to come back to Detroit.Eli Zaret joins the show to discuss the Detroit Lions ineptitude, a deep dive on MSU's running game, and rip on Jim Harbaugh.Generational Warfare: Millennial bosses cannot handle the Gen Z workplace demands.COP26 Climate Summit News: Joe Biden justifiably fell asleep. His polls are going the way of his eyelids. Wolf Blitzer has no idea what city is hosting the summit. Greta Thunberg is still angry.Migrants might get paid more than you.Kumar is out of the closet with both his sexuality and sports fandom.Demi Lovato met aliens.Karl's latest WATP features Anthony Cumia and destroys Virgin Mornings.Zooves was in bed before Halloween.Men are still better than woman... in the ring.Do bears menstruate?Drew has received a lot of feedback regarding his issues with CVS Pharmacy.Stan Edwards is really mad at 97.1 The Ticket.ML Elrick joins the show to remind people that he's running for Detroit City Council. You can listen to ML's podcast right here.A KISS roadie died in Detroit and everyone is upset at KISS.Rolling Stone Magazine is becoming Woke Magazine.Zayn Malik is getting dropped over the Gigi Hadid feud.Halloween: JLo went to JGar's neighborhood. Alec Baldwin took some time off shooting people to dress up with his kids. Ireland Baldwin made a poor costume decision.The Loudoun County School Board is doing great.The Washington Football Team and the NFL are straining to do some explaining.Jon Gruden is thinking about suing the NFL.No one seemed to care that much, but Kyle Busch is sorry for using the evil r-word.Some people still like sucking on boobies as adults.Charlie LeDuff had Dr. Robert Anderson victim, Jon Vaughn, on his last show. Chuck Christian reveals details of his abuse.Social media is dumb but we're on Facebook, Instagram and Twitter (Drew and Mike Show, Marc Fellhauer, Trudi Daniels and BranDon).
This Week in Machine Learning & Artificial Intelligence (AI) Podcast
Today we're joined by Hamel Husain, Staff Machine Learning Engineer at GitHub. Over the last few years, Hamel has had the opportunity to work on some of the most popular open source projects in the ML world, including fast.ai, nbdev, fastpages, and fastcore, just to name a few. In our conversation with Hamel, we discuss his journey into Silicon Valley, and how he discovered that the ML tooling and infrastructure weren't quite as advanced as he'd assumed, and how that led him to help build some of the foundational pieces of Airbnb's Bighead Platform. We also spend time exploring Hamel's time working with Jeremy Howard and the team creating fast.ai, how nbdev came about, and how it plans to change the way practitioners interact with traditional jupyter notebooks. Finally, talk through a few more tools in the fast.ai ecosystem, fastpages, fastcore, how these tools interact with Github Actions, and the up and coming ML tools that Hamel is excited about. The complete show notes for this episode can be found at twimlai.com/go/532.
The Hawk takes over, the Billionaire Tax, Righteous Rick: Candyman, Tiger King 2, American Crime Story: Impeachment, listeners in the Cayman Islands, and we do a wellness check on Count David Wimp.The Hawk is doing freelance voice work for us today since our drops are broken.Deshaun Watson is holding all the cards with his career and crimes.Nick Rolovich lost his head coaching gig with Washington State for refusing the jab despite his states mandate. ESPN tries to figure out what happened.Bill Gates is apparently the greatest villain in human history. Dave Grohl is doing something again. This time at the House of Blues... Cleveland.Drew is sad he can't hear Brown Sugar at the Stones concert.Righteous Rick is selling candy and beef jerky on Facebook. We find out why.Adam Levine was assaulted on stage by a fan and now he's seen as an elitist.We try another wellness check on Count David Wimp to get his take on Gibbs leaving NCIS.Zooves is wearing a mask indoors right now, but no word on if he does so in the bath.Floyd the Barber and FDR were polio pioneers.We all grieve differently. Jayne Rivera does so by posting sexy pictures of herself next to her dad's corpse.RIP former Detroit Lion Mike Lucci.Hilarious Baldwin's podcast has been canceled.Matthew Stafford was mic'd up this past Sunday.Kobe Bryant's wife had to find out about her husband and daughter's deaths with 'RIP Kobe' notifications.The Billionaire Tax is such a silly idea that it's already dead.Tiger King 2 is coming out soon and Marc is sucked back in.Vote for ML on Tuesday.We are the #2 podcast in the Cayman Islands. Some people are saying that some listeners just went on vacation there.LeBron James spoiled the ending of Squid Game and the creator is furious.The Cotton Club Murder is covered in The 1980s: The Deadliest Decade.American Crime Story: Impeachment just dropped another episode.The Bachelor is nothing without Chris Harrison.Enjoy more Clarktober.Social media is dumb but we're on Facebook, Instagram and Twitter (Drew and Mike Show, Marc Fellhauer, Trudi Daniels and BranDon).
Netflix walkout counter-protester Dick Masterson joins us, John Hinckley Jr joins Twitter, remembering Chuck Hughes, Jon Gruden breaks his silence, Maz checks in, duel Bonerlines, and Jim Fouts is still sizzling.Carlos Monarrez's heart must still be broken seeing that attempted murderer, Justin Turner, in the NLCS this year.What is race-norming? We find out. SIST: Najeh Davenport once pooped in a hamper.Enis Kanter got the Boston Celtics kicked out of China due to his take on Tibet.Dick Masterson and company crashed the Netflix protest over Dave Chappelle. Check out The Dick Show here and his terrific trolling of Dr. Phil right here. Jokes are funny.Kate Beckinsale is a genius. Just ask her like Howard Stern did for some reason.Jerkmate brings you the Bonerline. Thanks to our Forensic Accountant for compiling our questions in Q3.Jon Gruden says the truth will set him free.Remembering former Detroit Lion Chuck Hughes. 50 years ago, he became the only NFL player to die during a game.Drew wants to watch Dick Butkus highlights.John Hinckley Jr. is on Twitter now and he's quickly passing Drew in followers. He is announcing live shows!Charlie Murphy vs Darryl Stingley.The show gives multiple reasons to call Old Man Conrad back... but Drew isn't biting.WeWork is BACK.Donald Trump's new social media 'Truth Social' is bound to be the next hot TikTok for kids. It's already been hacked.Jim Fouts is still looking hot on local TV news tonight.Brian Laundrie is finally officially dead.In-N-Out Burger lost its battle with San Francisco's COVID-19 rules.Tom Mazawey joins us from his bowling league. Some people are saying his Atlanta Brave fandom mocks Native Americans.The Deshaun Watson trade rumors are heating up.Listen to ML Elrick and Shawn Windsor fight while ML's mom referees.Debra 'Everything I Touch Turns Into a' Messing apologizes to Kim Kardashian.Aimee Osbourne > Kelly Osbourne.The AGT stuntman is totally fine.There is a GoFundMe for a Fox 2 photog who has been recently paralyzed. Donate here.This week's Dateline will feature the Egypt Covington case.Drew is eating weiners for Harry Houdini at American Coney Island on Sunday.Enjoy more Clarktober!Social media is dumb but we're on Facebook, Instagram and Twitter (Drew and Mike Show, Marc Fellhauer, Trudi Daniels and BranDon).
The forecast calls for porno on KREM, Brian Laundrie body update with Bullhorn Andra, Netflix walkout/protest, WNBA parade attended by hundreds, and the Toolbox Killer leads us into a Foreigner/Asia rabbit hole.Drew's going to the Battle of the George Jewett as his first University of Michigan football game of the year.MLB Championship series have been pretty good. Joe Biden was heckled on Fox's post game coverage. Some baby took over Fenway way past his bedtime. Charles Barkley popped off on Kyrie Irving.Robin Roberts lied to her audience as the WNBA Championship parade attracted very few people to the streets of Chicago.KREM accidentally aired pornography. We call them to let them know.We try to reach the Sissy of Fremont Street after he posted his phone number online.Some dude ate a phone.Dirty Laundrie: Brian Laundrie's body was probably found today, but internet sleuths claim he's still out there using his Pinterest account. We chat again with Bullhorn Andra live from the Laundrie home.Brandon Goodwin is looking to get his COVID / NBA story out there. We offer him a platform.Chris Brown has Kyrie Irving's back.Alyssa Milano has been arrested and she's bragging about it.Meghan Markle is now making demands to Congress.Drew Crime: Don't murder your spouse on the day they file for divorce. Bonerliners have recommended The Toolbox Killer on Peacock. Nikolas Cruz blames weed for his massacre but we can only focus on the sexy judge in the courtroom.We rock out to Foreigner and realize that someone should make a bad Broadway musical with their catalog.WATP's Reddit sure hates Boomer Drew. Boomers are ruining homeowning for Millennials.Dave Grohl believe Nandi is as inspiring as the Beatles and Led Zeppelin combined."Dogs vs The Volcano" starring Tom Hanks.Gas Station Shootings: Stopping for gas in Detroit when it's nighttime seems very dangerous. The dude who killed a Detroit firefighter at a gas station in Troy is out on bond.Macomb schools can't feed their students. Dave Chappelle is so evil that people are protesting Netflix. There actually were some people there that still liked jokes.Richard Speck had great boobs and his boyfriend is one cool kat.Bitcoin is soaring and Zooves is loaded again.Eli may be making some appearances soon.ML's Soul of Detroit is getting feisty.Bob Page hates cigarettes and has no idea how Tom Petty died."The Batman" trailer is out.In case you haven't heard, the supply chain is an issue.Clarktober takes us back to James Brown and Tanith Belbin emails.Social media is dumb but we're on Facebook, Instagram and Twitter (Drew and Mike Show, Marc Fellhauer, Trudi Daniels and BranDon).
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