Applied AI Pod podcast

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تمت الإضافة منذ قبل five أعوام

المحتوى المقدم من Alexandra Petrus. يتم تحميل جميع محتويات البودكاست بما في ذلك الحلقات والرسومات وأوصاف البودكاست وتقديمها مباشرة بواسطة Alexandra Petrus أو شريك منصة البودكاست الخاص بهم. إذا كنت تعتقد أن شخصًا ما يستخدم عملك المحمي بحقوق الطبع والنشر دون إذنك، فيمكنك اتباع العملية الموضحة هنا https://ar.player.fm/legal.

Exile

1
Episode 10: From Refugee to Radical 44:09

منذ 2 years44:09

التشغيل لاحقا

قوائم

إعجاب

احب

44:09

When a young Eva Kollisch arrives as a refugee in New York in 1940, she finds a community among socialists who share her values and idealism. She soon discovers ‘the cause’ isn’t as idyllic as it seems. Little does she know this is the beginning of a lifelong commitment to activism and her determination to create radical change in ways that include belonging, love and one's full self. In addition to Eva Kollisch’s memoirs Girl in Movement (2000) and The Ground Under My Feet (2014), LBI’s collections include an oral history interview with Eva conducted in 2014 and the papers of Eva’s mother, poet Margarete Kolllisch, which document Eva’s childhood experience on the Kindertransport. Learn more at www.lbi.org/kollisch . Exile is a production of the Leo Baeck Institute , New York | Berlin and Antica Productions . It’s narrated by Mandy Patinkin. Executive Producers include Katrina Onstad, Stuart Coxe, and Bernie Blum. Senior Producer is Debbie Pacheco. Associate Producers are Hailey Choi and Emily Morantz. Research and translation by Isabella Kempf. Sound design and audio mix by Philip Wilson, with help from Cameron McIver. Theme music by Oliver Wickham. Voice acting by Natalia Bushnik. Special thanks to the Kollisch family for the use of Eva’s two memoirs, “Girl in Movement” and “The Ground Under My Feet”, the Sophia Smith Collection at Smith College and their “Voices of Feminism Oral History Project”, and Soundtrack New York.…

Applied AI Pod

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- This podcast show is currently on a break. - Real AI talks with real people. Startup founders, startup engineers, AI community leaders, research scientists, innovation leaders, product builders, passionate AI practitioners - we talk to everyone! Grab a rounded perspective on how AI is used, tradeoffs for specific AI tools or methods, challenges in the space of AI technologies, and its future. New to AI concepts? Try the ‘Elements of AI’ 6-chapters course for an introduction to AI, and Building AI. It’s world #1 AI MOOC. And join some AI communities or other relevant AI-centered groups. Podcast available on all popular podcasting platforms or via assistants like Google, Alexa, or Siri.

33 حلقات

#Tech #Entrepreneur #Business #Self-Improvement #Alexandra Petrus #Artificial Intelligence #Ai Use-cases #Ai Applications At Scale #Computer Vision #Ai Practitioners #Podcasting Education #Nlu #Applied AI #NLP

Applied AI Pod

12 subscribers

updated منذ 3 أعوام

منزل السلاسل•Feed

33 حلقات

كل الحلقات

Applied AI Pod

1
AI for Real Estate Customer Goals, E33 25:57

منذ 3 years25:57

25:57

Episode highlights: 01:00 - Conversational AI for the future of marketing and sales, focus on the real estate industry. 04:00 - How Structurely works and what it solves. 06:50 - Benefits to businesses utilizing AI within their companies. 10:55 - The future of real estate by use of machine learning. 16:10 - Creating a more promising future for AI as a tool for positive outcomes. E.g. Zillow. 23:00 - Conversational AI's next big challenges. References: Nate's LinkedIn profile Nate's Twitter profile Structurely's Company Website…

Applied AI Pod

1
Scalable Reliance on AI for e-Invoicing, and AI Principles, E32 47:43

منذ 3 years47:43

47:43

02:00 - Ada's performance, stories and metrics around. Size of the impact AI has in this space, as covered by Tradeshift. 05:35 - Working with AI/ML teams. 14:40 - Assessing how much data is needed for an AI project. 18:45 - Data risks. 24:25 - Is Agile good for AI teams? 27:30 - How much does UX matter in e-Invoicing and ML/Data projects? 36:35 - How can projects get derailed or fail? What should we watch out for. 40:05 - Funny fails. 41:50 - AI principles. References: Lloyd's Linkedin Profile Tradeshift's Ada technology Tradeshift's surpass of $1 trillion in transactions processed on their platform.…

Applied AI Pod

1
Voice AI from the space of VoiceSearch and VoiceServices, E31 49:33

منذ 3 years49:33

49:33

02:35 - Why hasn’t voice AI taken off already? 22:50 - Can we fulfil an end to end new purchase naturally? 32:20 - How can we resolve the disambiguation problem in NLU? 37:20 - Context and memory perspectives. 43:20 - How do we make conversations natural? References: Dustin's VUX World Podcast Dustin's Linkedin profile Hannes' LinkedIn profile Speechly's Twitter profile Speechly product search and checkout demo Speechly's Interspeech Research Paper 2021…

Applied AI Pod

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NLP, Speech Tech, Transformer Models, w/ Marc von Wyl, Algolia, E30 56:20

منذ 3 years56:20

56:20

01:15 - How does NLP work? 04:05 - How do Transformer-based NLP models work? 08:20 - How to look at unstructured data to take advantage of it more. 12:00 - How to leverage ML to bring more to unstructured data? 15:25 - Approach for low resources languages. 23:25 - Word embeddings for common reasoning needs. 26:55 - Techniques to follow to improve error and ambiguity in training data or for a model in general. 30:10 - Are GPTs leading effort in the field in a wrong direction? 34:15 - Is DeepLearning the end of AI? 37:20 - What are some good NLP metrics to watch? 42:05 - How do we get past transactional queries to conversational queries? 52:00 - Is the Turing test still relevant for NLP or has it become obsolete? References: AI-Powered Search referenced in respect of text not being unstructured. Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing Rethinking Search:Making Experts out of Dilettantes Common sense reasoning TWIML AI podcast 518 with Yejin Choi DARPA's Explainable AI Project EPITA is an engineering school in Paris. Marc's LinkedIn profile .…

Applied AI Pod

1
AI/ML Projects, Methodologies, Best Practices, E29 54:19

منذ 3 years54:19

54:19

12:50 - Is the Turing test still relevant? 21:30 - Why it's important to use methodologies in AI projects and what are some best practices out there fit for AI projects. 28:00 - Falsehoods of methodologies in AI projects. 35:00 - Is Agile a good framework for AI/ML projects/products? 40:10 - How can projects get derailed or fail if you don't have a plan in place. 44:20 - The best compliment one can get after building an AI project or system. 47:25 - Is DL the end of AI? References: CPMAI methodology Cognilytica's Voice Assistant Benchmark 1.0 and 2.0 AI Today podcast show with Alexandra Petrus as guest AI Today podcast show…

Applied AI Pod

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Developing Creativity with AI & DL for Sound & Audio, with Valerio Velardo, E28 57:48

منذ 4 years57:48

57:48

2:10 - Using AI to augment and reshape creativity in a modern world. Psychological creativity and story creativity - can an AI model help AI music artists, today, get off their creative blocks? 12:15 - Attempt to define ‘good’ music, using a cognitive music literature background. 17:00 - Are we better or worse off, for AI in audio/music? Is it sustainable for the effort input and cost, impact and efficiency output? 22:35 - ‘Deep Nostalgia” from myheritage initiative, and GPT-J - looking for strengths in the two approaches. 29:25 - The Sound of AI community - a HuggingFace version for audio? 31:15 - Train a DL - CNN sound classifier built with Pytorch and torchaudio on the Urban Sound 8k dataset. 35:00 - Is deep learning a dead end for artificial intelligence? 38:05 - Could someone that is a pure tech profile ever be in such an intersection in sync with the artistic world? Is it a pre-req to be domain savvy to build AI audio solutions? 42:10 - Helping music tech companies with a focus on audio (voice, speech, sound), the experience so far. 49:45 - Hard problems to solve when dealing with AI audio - Top three. 56:50 - First piece of music composed by a machine. References: The Sound of AI YT Channel: https://www.youtube.com/c/ValerioVelardoTheSoundofAI/featured Sign up for The Sound of AI Slack Community PyTorch for Audio + Music Processing https://www.youtube.com/watch?v=gp2wZqDoJ1Y&list=PL-wATfeyAMNoirN4idjev6aRu8ISZYVWm Audio Signal Processng for ML https://www.youtube.com/watch?v=iCwMQJnKk2c&list=PL-wATfeyAMNqIee7cH3q1bh4QJFAaeNv0 OpenSource Research project building a speech-operated neural synthesiser Deep Learning for Music https://github.com/ybayle/awesome-deep-learning-music Sweet Anticipation book: Music and the Psychology of Expectation by David Huron Valerio Velardo's LinkedIn The Frame Problem of AI…

Applied AI Pod

1
Green AI: by and for AI, with Kordel France - AI startup founder, E27 46:35

منذ 4 years46:35

46:35

1:50 - Using AI for the environment 6:55 - AI spices for agriculture 12:15 - AI in outdoor uses 15:15 - Green AI in Seekar's work 22:15 - Training AI models for a green AI approach 27:10 - Seekar in the medical space, and covid19 opportunities 39:15 - NLP tradeoffs and takeaways 43:10 - Similarities in practicing jiu-jitsu and AI References: Building AI models to be greener, and Seekar's Research Gate paper. This paper gives more insight into how Seekar was able to compress a large AI model down to a small enough size without compromising accuracy or performance. COVID-AI app from AppStore Exeda (Exploratory Emotional Detection Agent), mentioned in reference of using NLP for emotion recognition. Seekar's goal is to develop a psychological screening tool that can be downloaded as an app and used to check mental health daily through a 30-second voice recording in a similar manner as one brushes their teeth daily. 80% of personal communication happens through body language and Seekar’s products are utilizing this principle to better treat mental health. Research paper in progress.…

Applied AI Pod

1
Drive CX and Revenue with NLP in marketing and ecommerce, E26 44:39

منذ 4 years44:39

44:39

01:25 - Do NLP models need someone that is not completely monolingual? 05:20 - Types of NLP in marketing and/or e-commerce. 11:30 - Challenges in the e-commerce space: Behavioural data gathered by cookies has disappeared. 16:00 - Every 40 seconds, our attention breaks. Is that fact taken into account in NLP modeling for personalization? 18:20 - Models like GPT-3 open a whole new commercialization avenue in the marketing world, specifically for content creation. Impact of the wave. 21:50 - Is it fair to use an AI model for IP and content in such a way you influence millions of users on a website at once? 30:45 - Explainable models, debugging and how models could function. 37:00 - Provocative contexts for data scientists nowadays. 41:00 - Future of NLP. Episode references: GPT3 the beginning of a new app ecosystem Amazon makes Alexa Conversations generally available to developers Copy.AI and Taglines .AI based on GPT3. Other spinoffs in the same space: Copy Shark ; Snazzy AI ; experiments using platforms like VWO. Explainable models by DARPA NLP in Marketing, part 1 How virtual assistants (i.e. in your smartphone) understand you AI and NLP in marketing, webinar Katherine's Linkedin Katherine's Twitter Bucharest AI's meetup on Gender Imbalance, AI Mentorship & good delivery in AI…

Applied AI Pod

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Deep tech startups, VC investments, and deep problems, E25 1:05:21

منذ 4 years1:05:21

1:05:21

01:35 - Why did you decide to continue bootstrapping and decided to not opt for an investment. 06:50 - In the age of the million dollar supremacy how much money is a VC ready to invest. 08:56 Open source AI, good or bad idea? - VC and deep tech founder perspective. 14:15 - What’s the ideal shareholder split? 20:40 - Should one opt for Europe instead of Silicon Valley to raise capital faster? 23:10 - Effects of the pandemic on the deep tech investment space. 29:10 - Do VCs run their due diligence in their investment process + should VCs start considering checking reddit channels from now on? 32:45 - The gap between early stage deep tech startups and investments. 41:30 - Time, as an essential factor, in a deep tech startup - time from idea to prototype. 49:45 - How is a founder coping with the long development cycle from a cost / business model perspective. 55:00 - Pre-seed to seed stage, where is the role of AI/ML: core, feature, end-to-end, black box. 59:10 - How much is reusing vs. proprietary AI work. 01:01:15 - What does a VC scout do? Reference links: Alexander Piskunov's LinkedIn Amandine Flachs' LinkedIn Amandine Flachs' Twitter Venture Capital Scout Programs…

Applied AI Pod

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World’s #1 AI MOOC w/ creator Prof. Teemu Roos: AI Course, AI Perception, Finland, Education & Learning, E24 44:48

منذ 4 years44:48

44:48

02:43 - Motivation behind building a scaled MOOC AI course 06:40 - Effort behind an AI course to educate 1% of EU citizens 10:45 - Finland's heritage in education, and AI takeaways for course takers 20:55 - AI Challenge, or how are companies joining the AI education movement 25:45 - Digital spending priority: digital skills & education OR upgrading our health systems - Opinion 30:13 - Feels of a creator after building a popular AI course 36:55 - Ethics of AI course, and Elements of AI new chapters exploration References: Elements of AI Romania Elements of AI global version EU local Elements of AI Partners & movement Ethics of AI course Ready AI Finnish Center for AI Prof. Teemu Roos LinkedIn Prof. Teemu Roos Twitter Artificial Intelligence from Finland e-book…

Applied AI Pod

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AI in game development & UX for gamers, w/ Unity ML-Agents' PM, Jeffrey Shih, E23 41:32

منذ 4 years41:32

41:32

02:10 - Brief history of game development in relation to AI advancements 10:15 - Games driving advances in AI research: PR or reality? 15:50 - Latest AI technique popular in game development 20:55 - The role of Unity Game Simulation to reduce time & cost with games pre-launch testing 26:45 - What’s fancy in the games world 31:35 - Streaming a game vs. traditional edge processing, gamer’s lens 37:55 - What's next for games & AI References: Unity ML-Agents Toolkit GitHub Jeff's Twitter handle @shihzy Jeff's LinkedIn Host's notes: 2021 Update for AI advancements through game examples History of games at DeepMind Top AI Labs worldwide and AI's potential Facebook, Carnegie Mellon build first AI that beats pros in 6-player poker…

Applied AI Pod

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Game up: AI models, GPT, and Cyberpunk 2077, with former AI teacher, Virgil Ilian, E22 55:14

منذ 4 years55:14

55:14

2:00 - Hottest AI trends for 2021 5:35 - Open source for AI - paradigm shift 11:30 - AI model supremacy 21:10 - Authorship rights when AI contributes 31:00 - GPT encapsulating knowledge? 34:00 - Human consciousness replicable as computation 41:50 - Are we in a matrix? 42:30 - Cyberpunk 2077 50:50 - Can AI create emotion the way we cannot tell it is AI? Conversation references: Book: " You look like a thing and I love you" - Janelle Shane Book: "Shadows of the Mind", Roger Penrose Chinese Room argument Manhattan project Art Breeder project The Origin of Circuits - re FPGA topic Host's notes: Gartner Top Strategic Technology Trends for 2021 Jukebox - music-making tool by OpenAI. While the achievement is significant from a technological perspective, the results are unlikely to threaten the livelihoods of human musicians. DALL·E generates images in response to written inputs, and (whose name honours both Salvador Dalí and Pixar’s WALL·E ) is a decoder-only transformer model. From Andrew Ng's 'The Batch' newsletter : OpenAI trained it on images with text captions taken from the internet. Given a sequence of tokens that represent a text and/or image, it predicts the next token. Then it predicts the next token given its previous prediction and all previous tokens. This allows DALL·E to generate images from a wide range of text prompts and to generate fanciful images that aren’t represented in its training data, such as “an armchair in the shape of an avocado.” WHY it matters? As Ilya Sutskever puts it ‘combining language and vision techniques could overcome computer vision’s need for large, well labeled datasets’.…

Applied AI Pod

1
#BeAIStartup: WIYO - matches recommendation for professionals, E21 19:01

منذ 4 years19:01

19:01

Why do you do what you do? Using big data and AI to connect big groups - how is that going and what are you current challenges? How does a customer journey usually go. Take the example of the BeAI community, what would the journey look for us? “Share your travel plans with your whole network or just a few selected friends and see if any of your plans match”, do you find it hard to resonate with people given the pandemic and limitation of travels? Have you pivoted on this USP? Reference links: WIYO website…

Applied AI Pod

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Product research teams, AI in Finance, and D&I with Wendy Tay - scientist-turned-PM @BorealisAI, E20 23:28

منذ 4 years23:28

23:28

Notes: The role of a PM in a research environment Recurring skills needed for an AI PM to have successful products built and good communication with both researchers and business types AI model governance and why is important in banking Where can AI help in the banking industry What is responsible AI Borealis and RBC initiatives to help with social good causes and women in AI Diversity and Inclusion - what it means and why it matters for product management Top things for a PM in a research project journey Reference links: Respect AI Initiative Borealis AI Wendy’s LinkedIn…

Applied AI Pod

1
#BeAIStartup: EVAAI - replicate personalities as AI assistants for mental health, E19 18:10

منذ 4 years18:10

18:10

5000+ likes on Facebook, that is a good crowd for a startup, how did you build this? Current tech stack and challenges. Current increased online consumption and trends versus your solution - how do you see everything evolving? What are the languages covered? Reference links: EVAAI Website EVAAI Facebook Page…

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