Podcasts about speech api

Howdy, Alex here, let me catch you up on everything that happened in AI: (btw; If you haven't heard from me last week, it was a Substack glitch, it was a great episode with 3 interviews, our 3rd birthday, I highly recommend checking it out here) This week was started on a relatively “chill” note, if you consider Anthropic enabling 1M context window chill. And then escalated from there. We covered the new GPT 5.4 Mini & Nano variants from OpenAI. How MiniMax used autoresearch loops to improve MiniMax 2.7, Cursor shipping their own updated Composer 2 model, and how NVIDIA CEO Jensen Huang embraced OpenClaw calling it “the most important OSS software in history” and that every company needs an OpenClaw strategy. Also, OpenAI acquires Astral (ruff, uv tools) and Mistral releases a “small” 119B unified model and Cursor dropped their Opus like Composer 2 model. Let's dive in: ThursdAI - Highest signal weekly AI news show is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.Big Companies LLMs 1M context is now default for Opus.Anthropic enabled the 1M context window they shipped Claude with in beta, by default, to everyone. Claude, Claude Code, hell, even inside OpenClaw if you're able to get your Max account in there, are now using the 1M long version of Opus. This is huge, because, while its not perfect it's absolutely great to have 1 long conversation and not worry about auto-compaction of your context. As we just celebrated our 3rd anniversary, I remember that back then, we were excited to see GPT-5 with 8K context. Love how fast we're moving on this. OpenAI drops GPT-5.4 mini and nano, optimized for coding, computer use, and subagents at a fraction of flagship costLast week on the show, Ryan said he burned through 1B (that's 1 billion) tokens in a day! That is crazy, and there's no way a person sitting in front of a chatbot can burn through this many tokens. This is only achieved via orchestration. To support this use-case, OpenAI dropped 2 new smaller models, cheaper and faster to run. GPT 5.4 Mini achieves a remarkable 72.1% on OSWorld Verified, which means it uses the computer very well, can browse and do tasks. 2x faster than the previous mini, at .75c/1M token, this is the model you want to use in many of your subagents that don't require deep engineering. This is OpenAI's ... sonnet equivalent, at 3x the speed and 70% the cost from the flagship. Nano is even crazier, 20 cents per 1M tokens, but it's not as performant, so I wouldn't use it for code. But for small tasks, absolutely. Here's the thing that matters, these models are MEANT to be used with the new “subagents” feature that was also launched this week in Codex, all you need to do as... ask! Just tell Codex “spin up a subagent to do... X” and it'll do it.OpenAI shifts focus on AI for engineering and enterprise, acquires Astral.sh makers of UV. Look, there's no doubt that OpenAI the absolutely leader in AI, brought us ChatGPT, with over 900M users using it weekly. But they see what every enterprise sees, developers are MUCH more productive (and slowly so are everyone else) when they use tools that can code. According to WSJ, OpenAI executives will reprioritize some of the side-quests they have (Sora?) to focus on productivity and business. Which essentially means, more Codex, more Codex native, more productivity tools.With that focus, today they announced that OpenAI / Codex is acquiring Astral, the folks behind the widely popular UV python package manager. This brings strong developer tools firepower to the Codex team, the astral folks are great at writing incredibly fast tools in rust! Looking forward to see how these great folks improve Codex even more. Jensen Declares Total OpenClaw Victory at GTC, Announces NemoClaw (Github)This was kind of surreal, NVIDIA CEO Jensen Huang, is famous for doing his stadium size keynote, without a teleprompter, and for the last 10 minutes or so, he went all in on OpenClaw. Calling it “the most important OSS software in history” and outlining how this is the new computer. That Peter Steinberger with OpenClaw showed the world a blueprint for the new coputer, an personal agentic system, with IO, files, computer use, memory, powered by LLMs. Jensen did outline that the 3 things that make OpenClaw great are also the things that enterprises cannot allow, write access to your files + ability to communicate externally is a bad combo, so they have launched NemoClaw.They've got a bunch of security researchers to work with OpenClaw team to integrate their new OpenShell sandboxing effort, network guardrails and policy engine integration. I reminded folks on the pod that the internet was very insecure, there was a time where folks were afraid of using their creditcards online. OpenClaw seems to be speed running that “unsecure but super useful” to “secure because it's super useful” arc and it's great to see a company as huge as NVIDIA embrace. Not to mention that given that agents can run 24/7, this means way more inference and way more chips sold for NVIDIA so makes sense for them, but still great to see!Manus “my computer” and other companies replicating “OpenClaw” successThis week it became clear, after last weeks Perplexity “computer”, Manus (now part of Meta) has also announced a local extension of their cloud agents, and those two are only the first announcements, it's clear now that every company dissected OpenClaw's moment and will be trying to give its users what they want. An agentic always on AI assistant with access to the users files, documents etc. Claude code added “channels“ support with telegram and discord connectors today, which, also, is one big missing piece of the puzzle for them. Everything is converging on this. Even OpenAI is rumored to consolidate Codex (which sees huge success) with OpenAI and Atlast browser into 1 “mega” APP that would do these things and act as an agent. ThursdAI - Highest signal weekly AI news show is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.MiniMax M2.7: The Model That Built Itself This one blew me away, it's not quite open source (yet?) but the MiniMax folks are coming out with a 2.7 version just after their MiniMax 2.5 was featured on our show and .. they are claiming that this model trained itself. Similarly to Andrej Karpathy's auto-researcher, the MiniMax folks ran 100+ autonomous optimization loops, t get this model to 56.22% on the hard Swe-bench pro benchmark (close to Opus's 57.3%!) and this one gets a 88% win rate vs the very excellent MiniMax 2.5. They used the previous model to build the agent harness and scaffolding, with 1 engineer babysitting these agent, and writing 0 lines of human code, which as we said before, every company will be doing, as we're staring singularity in the face! We've evaluated this model as well (Wolfram has been busy this week!) and it's doing really well on WolfBench with 52% average and 64% top score, it's very close to 5.3 codex on our terminalBench benchmark! We hope that this model will be open source at some point soon as well! Cursor drops Composer 2 - nearly matching Opus 4.6, fast version (Blog)Cursor decided to add to our show's breaking news record of Thursday releases with a brand new in-house trained Composer 2. This time they released more benchmarks than only their internal “composer bench” and this model looks great! (we are pretty sure it's a finetune of a chinese OSS model, but we don't know which) Getting 61% on Terminal Bench, beating Opus 4.6 is quite a significant achievement, but coupled with the incredible pricing they are offering, $0.5/1Mtok input and $2.50/M output tokens, Cursor is really aiming for the productivity folks and showing that they are more than just an IDE.Early users are reporting noticeably cleaner code than both Opus and Composer 1.5 — better adherence to clean code principles, smarter multi-file implementations, and strong performance on long-horizon agentic tasks like full API migrations and legacy codebase refactoring. They also shipped a new interface called Glass (in alpha) that's built for monitoring these long-running agent loops. Open Source: Mistral is Back, BabyMistral Small 4: 119B MoE with 128 experts + Apache 2.0 (X, Blog, HF)It's been a while since Mistral dropped something properly open source, and this week they kicked off what looks like their fourth generation with Mistral Small 4. The name is a little funny given the actual size — 119 billion total parameters, 128 experts in the mixture — but with only 6 billion active per token. So you get the knowledge footprint of a massive model but the compute profile of a small one. Very MoE-brained.The bigger story here is what's unified inside: this is Magistral (reasoning), Pixtral (multimodal), and Devstral (coding) all rolled into one weights file. Previously you had to choose which Mistral “side quest” model you wanted. Now there's a reasoning_effort parameter where you dial from none for fast cheap responses all the way up to high for step-by-step thinking, no model switch required. How does it perform? We ran it through WolfBench and it landed toward the lower end of Wolfram's current leaderboard — around 17% on the agentic tasks, roughly on par with Nemotron at the same scale. It's not competing with Opus or GPT-5.4, and we weren't really expecting it to. What we're excited about is that it does multimodal, reasoning, and coding in one Apache-licensed package, and people are already running IQ4 quants locally. Shout out to Mistral for the return to open source — it's been a minute, and the community noticed.Unsloth Studio: Fine-Tuning Gets a UI (Blog)Something I think people are sleeping on this week is Unsloth Studio, the open-source web UI that the Unsloth team just launched for local LLM training and inference. Unsloth has been quantizing and compressing models better than basically anyone for a while now — 2x training speed, 70% less VRAM, zero accuracy loss — but that was all code-first. Studio is the no-code interface layer on top of all of that.The numbers: supports 500+ models across text, vision, audio, and embeddings. It runs 100% offline with no telemetry. Julien Chaumond, the CTO of Hugging Face, confirmed it trains successfully on a Colab Pro A100. There's even a free Colab notebook for models up to 22B parameters. For folks who want to fine-tune models overnight without spinning up cloud infra or wrestling with Docker, this is a genuine leap forward. Nisten compared it to what LM Studio did for local inference — making something that used to require deep expertise suddenly accessible to anyone. I think that comparison is spot on, and I want to get Daniel and the Unsloth team on the show to dig into this properly.This Week's Buzz: W&B iOS App & The Overthinking ParadoxThe iOS App is Finally Here (app store)Okay, I'm going to do a quick applause.

Vida Unveils New AI Voice Capabilities with OpenAI's Realtime Speech-to-Speech API Integration, Podcast, Vida's expanded Partner and Reseller Programs empower telecom providers and MSPs to offer these cutting-edge capabilities directly to their customers “This product was built from the ground up with the MSP in mind,” says Lyle Pratt of Vida. In this podcast, we explore Vida's groundbreaking integration of OpenAI's Realtime API, which brings emotionally expressive, multilingual capabilities to its AI voice platform. As an emerging leader in AI voice solutions, Vida is among the first to leverage this advanced technology, enabling businesses to deliver customer interactions that feel more natural and engaging. The discussion highlights how features like tone modulation and laughter add a human touch to automated conversations, helping businesses boost productivity and increase revenue. The episode also delves into Vida's expanded Partner and Reseller Programs, which empower telecom providers and MSPs to offer these cutting-edge capabilities directly to their customers. Vida shares its vision for the future of AI voice technology, showcasing how emotionally intelligent agents can transform customer experiences across industries. This conversation provides valuable insights for businesses harnessing innovative AI voice solutions to stay competitive in a rapidly changing tech landscape. About Vida Vida is a leading provider of enterprise-grade AI voice solutions, transforming the way telecom service providers and small to medium-sized businesses operate. Vida's AI voice agents automate key business functions such as customer service, lead qualification, scheduling and sales. Founded by telecom industry veterans, Vida's proprietary voice stack integrates seamlessly with existing telecom networks and business phone systems over SIP. Leveraging advanced AI technology, Vida delivers lifelike, low-latency voice interactions for real-time, engaging conversations. For more info, please visit https://vida.io.

Last week was another big week in technology. Google's NotebookLM introduced its Audio Overview feature, enabling users to create customizable podcasts in over 35 languages. OpenAI followed with their real-time speech-to-speech API, making voice integration easier for developers, while Pika's 1.5 model made waves in the AI world.In this episode, we chat with the a16z Consumer team—Anish Acharya, Olivia Moore, and Bryan Kim—about the rise of voice technology, the latest AI breakthroughs, and what it takes to capture attention in 2024. Anish shares why he believes this could finally be the year of voice tech. Resources: Find Olivia on Twitter: https://x.com/omooretweetsFind Anish on Twitter: https://x.com/illscienceFind Bryan on Twitter: https://x.com/kirbyman01 Stay Updated: Let us know what you think: https://ratethispodcast.com/a16zFind a16z on Twitter: https://twitter.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zSubscribe on your favorite podcast app: https://a16z.simplecast.com/Follow our host: https://twitter.com/stephsmithioPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.

Are you ready for a world where AI and AR are seamlessly integrated into our daily lives? The pace of innovation in these fields is accelerating rapidly, with major announcements from tech giants like OpenAI and Meta reshaping the landscape. In this episode, Chris Saad and Amir Shevat dive deep into the latest developments in AI and AR, exploring their implications for startups, developers, and society at large. In This Episode, You Will: Discover the latest revelations from OpenAI's Dev Day and why the new developer tools, like the Speech-to-Speech API and image fine-tuning, could be a game-changer for startups. Learn about the 98% cost reduction in AI models and how it could drastically lower barriers for developers. Unpack the ongoing drama at OpenAI, including the mass resignation of executives and speculation surrounding Sam Altman's control of the company. Understand the impact of OpenAI's shift to a B Corp structure and what it means for the future of AI and mission-based goals. Dive into Google's $2.7 billion rehire of an AI rockstar and why top-tier talent is driving astronomical valuations. Explore Meta's Orion AR glasses and consider their potential to replace smartphones—could this be the beginning of a new tech era? Consider how augmented reality will change our daily interactions and whether the future of AI lies in wearable tech like glasses and earbuds. Get insights into the cultural shift AR glasses may bring and the ethical considerations of such pervasive tech in our lives. The Pact Honour The Startup Podcast Pact! If you have listened to TSP and gotten value from it, please: Follow, rate, and review us in your listening app Subscribe to the TSP Mailing List at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://thestartuppodcast.beehiiv.com/subscribe⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Secure your official TSP merchandise at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://shop.tsp.show/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Follow us on YouTube at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.youtube.com/@startup-podcast⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Give us a public shout-out on LinkedIn or anywhere you have a social media following. Key links The Startup Podcast is sponsored by Vanta. Vanta helps businesses get and stay compliant by automating up to 90% of the work for the most in demand compliance frameworks. With over 200 integrations, you can easily monitor and secure the tools your business relies on. For a limited-time offer of US$1,000 off, go to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.vanta.com/tsp⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Get your question in for our next Q&A episode: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://forms.gle/NZzgNWVLiFmwvFA2A⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ The Startup Podcast website: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://tsp.show⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Learn more about Chris and Yaniv Work 1:1 with Chris: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠http://chrissaad.com/advisory/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Follow Chris on Linkedin: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.linkedin.com/in/chrissaad/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Follow Yaniv on Linkedin: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.linkedin.com/in/ybernstein/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Credits Editor: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Justin McArthur⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Content Strategist: Carolina Franco Intro Voice: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jeremiah Owyang⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

Our 142nd episode with a summary and discussion of last week's big AI new. Apologies for this one coming out after a pause, episodes will resume being released regularly as of this week. Read out our text newsletter and comment on the podcast at https://lastweekin.ai/ Email us your questions and feedback at contact@lastweekin.ai Timestamps + Links: (00:00) Intro / Banter Tools & Apps(03:00) Introducing PlayHT 2.0 Turbo ⚡️ - The Fastest Generative AI Text-to-Speech API (07:15) YouTube Music now lets you make your own playlist art with AI (09:23) Sick of meetings? Microsoft's new AI assistant will go in your place (11:54) Anthropic brings Claude AI to more countries, but still no Canada (for now)  Applications & Business(14:55) Humanoid robots face a major test with Amazon's Digit pilots (18:40) Figure 01 humanoid takes first public steps (22:31) AI-generating music app Riffusion turns viral success into $4M in funding (23:35) ChatGPT Creator Partners With Abu Dhabi's G42 in Middle East AI Push (25:00) AMD Scores Two Big Wins: Oracle Opts for MI300X, IBM Asks for FPGAs (26:38) Alibaba, Tencent among investors in China's rival to OpenAI with $341 million funding (30:35) AI companies drive demand for office space in tech hubs, new study finds (32:13) OpenAI is in talks to sell shares at an $86 billion valuation Projects & Open Source(35:00) Introducing Video-To-Text and Pegasus-1 (80B) (39:35) Adept Releases Fuyu-8B for Multimodal AI Agents (42:03) MiniGPT-v2: large language model as a unified interface for vision-language multi-task learning (44:53) Meta's Habitat 3.0 simulates real-world environments for intelligent AI robot training (48:22) DeepMind UniSim simulates reality to train robots, game characters  (49:13) Jina AI Launches World's First Open-Source 8K Text Embedding, Rivaling OpenAI (51:13) Llemma: An Open Language Model For Mathematics Research & Advancements(53:22) Eliciting Human Preferences with Language Models (57:23) New Nvidia AI agent, powered by GPT-4, can train robots (01:01:38) Unveiling the General Intelligence Factor in Language Models: A Psychometric Approach (01:04:48) AgentTuning: Enabling Generalized Agent Abilities for LLMs (01:09:51) Contrastive Prefence Learning: Learning from Human Feedback without RL (01:11:25) ‘Mind-blowing' IBM chip speeds up AI  Policy & Safety(01:14:57)  GM Cruise unit suspends all driverless operations after California ban (01:18:52) AI researchers uncover ethical, legal risks to using popular data sets (01:22:22) AI Safety Summit: day 1 and 2 programme (01:25:23) Anthropic's AI chatbot Claude is posting lyrics to popular songs, lawsuit claims (01:26:38) Mike Huckabee says Microsoft and Meta stole his books to train AI (01:27:10) Clearview AI Successfully Appeals $9 Million Fine in the U.K. (01:28:11) North Korea experiments with AI in cyber warfare: US official (01:30:17) OpenAI forms new team to assess ‘catastrophic risks' of AI UK poised to establish global advisory group on AI Synthetic Media & Art(01:32:22) This new data poisoning tool lets artists fight back against generative AI (01:34:32) Amazon now lets advertisers use generative AI to pretty up their product shots (01:36:36) The Beatles: ‘final' song Now and Then to be released thanks to AI technology

Scott Stephenson, CEO of Deepgram, joins SlatorPod to talk about his unique journey to co-founding the deep tech, automatic speech recognition (ASR) company and raising over USD 50m in funding.Scott recalls how his experience working with dark matter detectors as a particle physicist in China led to him becoming a deep-learning entrepreneur. He discusses some challenges in solving ASR; from labeling data for machine learning to formulating and executing an effective go-to-market strategy.The CEO gives his thoughts on Whisper, OpenAI's open-source ASR model, and how it may actually grow the total addressable market for voice AI companies. He shares the difficulties when it comes to translating a transcript versus translating straight from audio into another language.Scott gives his advice on how to build a successful AI company and appeal to investors. The pod rounds off with Deepgram's roadmap for the next year, with text to speech, voice cloning, real-time translation, and sentiment analysis being potential step changes in their growth trajectory.First up, Florian and Esther catch up on the language industry news from the past month, with Google announcing the launch of Translation Hub, its enterprise-scale document translation service.Esther discusses some of the language highlights from Netflix's third-quarter earnings call, including the titles of some of the best-performing non-English content. Meanwhile, Zoo Digital's share price was at a near all-time high as they weighed in at an almost USD 170m market cap.The duo also talk about funding, where multilingual AI writer Jasper announced it had raised USD 125m in its unicorn-making series A, which valued the startup at USD 1.5bn. And, after a dip in the Slator Language Industry Job Index in September, the LIJI defied expectations of a slowdown as it reached an all-time high in November.

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This week, we introduce Joe and Aisha, and welcome back Kate! We talk about Node JS, our Node projects and hear about Aisha's experiences since finishing FAC. We hope to get her back on to chat more about her experiences as a mentor in Gaza, too. The Founders & Coders (FAC) podcast is aimed at anyone interested in hearing about what it's like to be on the course, web development in general, and/or the backgrounds and interests of the people taking it. As the episodes progress, we'll try to make it more polished, and get the chance to include people otherwise associated with FAC (the people taking the FAC course in Nazareth and Gaza, FAC alumni, and some of the external speakers that we get in). Resources: Node JS: https://www.w3schools.com/nodejs/nodejs_intro.asp https://medium.freecodecamp.org/what-exactly-is-node-js-ae36e97449f5 (see comments in the article, too) https://developer.mozilla.org/en-US/docs/Learn/Server-side/Express_Nodejs/Introduction Context switching: https://www.linkedin.com/pulse/context-switching-developers-paul-graham/ Technical debt: https://en.wikipedia.org/wiki/Technical_debt Datasets subreddit: https://www.reddit.com/r/datasets/ https://www.reddit.com/r/datasets/comments/8ej8vh/the_446_people_places_and_things_donald_trump_has/ (and see the useful comment by rarely_beagle!) Speech API: https://developer.mozilla.org/en-US/docs/Web/API/Web_Speech_API NPM: https://nodesource.com/blog/an-absolute-beginners-guide-to-using-npm/ https://www.sitepoint.com/beginners-guide-node-package-manager/ ("beginners guide", but still technical) DRY code: https://www.codementor.io/joshuaaroke/dry-code-vs-wet-code-89xjwv11w Array and object methods and properties: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Array https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Object#Methods_of_the_Object_constructor Wes Bos' array cardio: https://www.youtube.com/watch?v=HB1ZC7czKRs Codebar: https://codebar.io/ Nikhila Ravi: https://twitter.com/nikhilaravi CORS: https://medium.com/@baphemot/understanding-cors-18ad6b478e2b (see article comments, too) Recommendations and where to find us: Aisha: http://www.askelias.club/ - may take a few seconds to load Fun Fun Function: https://www.youtube.com/channel/UCO1cgjhGzsSYb1rsB4bFe4Q Joe: https://www.instagram.com/joesfriel/ The Adam Buxton Podcast: http://adam-buxton.co.uk/podcasts A Neuroscientist Explains Podcast: https://www.theguardian.com/science/series/a-neuroscientist-explains-podcast Dom: https://twitter.com/dominicdigital All Songs Considered Podcast: https://www.npr.org/podcasts/510019/all-songs-considered?t=1535720672931 Stuff To Blow Your Mind Podcast: https://www.stufftoblowyourmind.com/podcasts The Vanilla JS Podcast: https://vanillajspodcast.com/ (good info, but a few episodes include quite a bit of course promo) Kate: https://twitter.com/sbinlondon DevPal: https://devpal.io/ Glitch: https://glitch.com/ Singing Cowboy Meme: https://www.youtube.com/watch?v=yBLdQ1a4-JI

Dopo aver ascoltato su youtube il seguente video: https://www.youtube.com/watch?v=AnX3Llzs9Asl’ho scaricato , convertito in mp3 e ho ottenuto il testo scritto tramite Speech API e Soundflower1.Introduzione musicale 2.Inizio ( io) il discorso registrando la prima parte dell’audio del video che mi sono trascritta tramite Soundflower:> ERMINIA FRANCA PERRICONE:“Trascrivere automaticamente e gratuitamente i miei file audio o il video… è molto semplice… devo partire da un file audio e utilizzerò le Google Speech API e Soundflower. Dove trovo le Google Speech API? E’molto semplice posso andare su Google e cercare Google Speech API e verrò portato nei risultati alla possibilità di vedere la dimostrazione di queste Google Speech API. A questo punto… setto la lingua italiana e poi devo fare in modo che il browser abbia in ingresso l'audio del file che vado a riprodurre e per fare questo mi serve Soundflower …che manderà in loop il programma che riproduce il mio audio con l'ingresso del browser .L'ingresso audio del browser …dopo che l'avrò installato andando nelle preferenze di sistema…nella parte audio …potrò trovare tra le fonti l'ingresso Soundflower 2ch …lo seleziono e chiudo le mie preferenze e vado ad aprire il mio file con …per esempio …con VLC …VLC riproduce file audio e file video…in maniera molto semplice… e quindi aperto VLC…una volta aperto VLC… apri file… mi posso anche aprire un recente perché l'ho trovato …” 3.File vocale originale ritagliato dal video di youtube e inserito in continuità alla mia registrazione che riporta le parole dell’autore:>AUTORE DEL VIDEO SU YOU TUBE:“Non ci vuole dare retta VLC …ci riproviamo …eccola qua… Allora è partita già in riproduzione e… vedi qui fa vedere il tempo che avanza…la puntata è partita in riproduzione, ma non la sto sentendo…perché non la sto sentendo? Perché sono già andato in audio e ho selezionato come periferica audio Soundflower 2ch… quindi VLC manda l'uscita audio… manda l'audio su questo canale 2ch…Soundflower 2ch…che è anche l'audio d'entrata del sistema operativo. Infatti, ora vado su web Speech API demonstration, clicco registra e, in questo momento, mi accorgo che sta registrando, ma non sta registrando quello che sto dicendo io… sta registrando quello che sta dicendo il file audio… che è il file che voglio trascrivere e questa trascrizione sarà accurata …dipende anche dal file audio… dal tipo di modo di parlare, comunque sarà abbastanza accurata.Io la trovo molto efficace ,anche perché questo motore, queste API si agganciano al motore di Google che è uno dei più avanzati al mondo per il riconoscimento vocale che è quello che funziona su tutti i telefoni Android e funziona anche su …sul riconoscimento …sulla ricerca vocale di Google” …4.Continuo ( io) il discorso registrando il prosieguo e aggiungendo la chiusura :“…quando avrò terminato la mia trascrizione potrò fare stop e copiare e andarla a incollare in qualsiasi blocco note per la revisione ,quindi potrò controllare …magari ascoltando il file e aggiustare questa trascrizione che però già è stata fatta automaticamente da Google”. E con questo è finito il mio compito Soundtrack:STOP!5.Chiusura musicalePUBBLICAZIONE SOUNDTRACK SU: https://www.spreaker.com

Jessica Forde, Yuvi Panda and Chris Holdgraf join Melanie and Mark to discuss Project Jupyter from it’s interactive notebook origin story to the various open source modular projects it’s grown into supporting data research and applications. We dive specifically into JupyterHub using Kubernetes to enable a multi-user server. We also talk about Binder, an interactive development environment that makes work easily reproducible. Jessica Forde Jessica Forde is a Project Jupyter Maintainer with a background in reinforcement learning and Bayesian statistics. At Project Jupyter, she works primarily on JupyterHub, Binder, and JuptyerLab to improve access to scientific computing and scientific research. Her previous open source projects include datamicroscopes, a DARPA-funded Bayesian nonparametrics library in Python, and density, a wireless device data tool at Columbia University. Jessica has also worked as a machine learning researcher and data scientist in a variety of applications including healthcare, energy, and human capital. Yuvi Panda Yuvi Panda is the Project Jupyter Technical Operations Architect in the UC Berkeley Data Sciences Division. He works on making it easy for people who don’t traditionally consider themselves “programmers” to do things with code. He builds tools (e.g., Quarry, PAWS, etc.) to sidestep the list of historical accidents that constitute the “command line tax” that people have to pay before doing productive things with computing. Chris Holdgraf Chris Holdgraf is a is a Project Jupyter Maintainer and Data Science Fellow at the Berkeley Institute for Data Science and a Community Architect at the Data Science Education Program at UC Berkeley. His background is in cognitive and computational neuroscience, where he used predictive models to understand the auditory system in the human brain. He’s interested in the boundary between technology, open-source software, and scientific workflows, as well as creating new pathways for this kind of work in science and the academy. He’s a core member of Project Jupyter, specifically working with JupyterHub and Binder, two open-source projects that make it easier for researchers and educators to do their work in the cloud. He works on these core tools, along with research and educational projects that use these tools at Berkeley and in the broader open science community. Cool things of the week Dragonball hosted on GC / powered by Spanner blog and GDC presentation at Developer Day Cloud Text-to-Speech API powered by DeepMind WaveNet blog and docs Now you can deploy to Kubernetes Engine from Gitlab blog Interview Jupyter site JupyterHub github Binder site and docs JupyterLab site Kubernetes site github Jupyter Notebook github LIGO (Laser Interferometer Gravitational-Wave Observatory) site and binder Paul Romer, World Bank Chief Economist blog and jupyter notebook The Scientific Paper is Obsolete article Large Scale Teaching Infrastructure with Kubernetes - Yuvi Panda, Berkeley University video Data 8: The Foundations of Data Science site Zero to JupyterHub site JupyterHub Deploy Docker github Jupyter Gitter channels Jupyter Pop-Up, May 15th site JupyterCon, Aug 21-24 site Question of the week How did Google’s predictions do during March Madness? How to build a realt time prediction model: Architecting live NCAA predictions Final Four halftime - fed data from first half to create prediction on second half and created a 30 second spot that ran on CBS before game play sample prediction ad Kaggle Competition site Where can you find us next? Melanie is speaking about AI at Techtonica today, and April 14th will be participating in a panel on Diversity and Inclusion at the Harker Research Symposium

It’s VMworld this week, so there’s fresh news from the Dell Technologies universe to sort through. VMware releases it’s SDDC on AWS scheme and Pivotal announces its container service/stack, Pivotal Container Service (PKS). We discuss both, including a meandering overview of what PKS is and some theory about what enterprises actually want with all that VMware in public cloud. Also, the tragic story of airline and hotel upgrades, like pearls to tired business travelers. Misc. Australia is bigger than France (http://imgur.com/z02XGzQ). Checks out (http://www.texasmonthly.com/the-daily-post/how-big-is-texas-compared-to-other-land-masses/). Coté got the SSSS TSA search. What fun! Now you can buy kubernetes from Dell https://pbs.twimg.com/media/DIlS4bPUQAEcO6Y.jpg:small VMware/Pivotal/Google make a kubo distro (https://blogs.vmware.com/cloudnative/2017/08/29/vmware-pivotal-container-service/). Uses BOSH, NSX, and kubo to setup clusters. Will run on vSphere and Google Cloud, promises to work with other Google Cloud services, be continuously updated to be compatible with GCE containers. Also, VMware storage services and comparability with VMware systems management tools. El Reg coverage (https://www.theregister.co.uk/2017/08/30/google_vmware_and_pivotal_team_for_onpremises_kubernetes/), and also from The New Stack (https://thenewstack.io/pivotal-container-service-hard-wires-cloud-foundry-kubo-google-cloud/). TPM (https://www.nextplatform.com/2017/08/29/vmwares-platform-revolves-around-esxi-except-cant/): “The private PKS stack will use vSAN for storage, vRealize Automation for orchestration and governance, vCloud Director for provisioning, and vRealize Operations for monitoring. (So, in theory, one could run the PKS stack on the AWS cloud slices that VMware has partnered with Amazon to create, effectively creating a clone of GKE to run on AWS bare metal iron. . . .)” More laundry listing of the parts from Google (https://www.blog.google/topics/google-cloud/vmware-and-pivotal-launch-new-hybrid-kubernetes-solution-optimized-gcp/), that is, Google Cloud services you can use in a PKS environment: BigQuery, Bigtable, Spanner, Storage, SQL, Pub/Sub, Vision API, Speech API, Natural Language API, Translate API. A list of capabilities (https://twitter.com/cloudnativeapps/status/902674269125042176) from Cornelia’s(?) talk, and what BOSH does (https://twitter.com/cloudnativeapps/status/902607633168818176) (and, thus, does in k8 management). Use it for (https://pivotal.io/pks): “PKS™ is ideal for workloads like Spark and ElasticSearch, and when you need access to infrastructure primitives. Further, use PKS for apps that require specific co-location of container instances, and for those that need multiple port binds.” The Pod affinity thing here is for when you want to run multiple things grouped together, like with Spark, Elastic Search, etc. where you the different things go together. More value-props’ing (https://twitter.com/cloudnativeapps/status/902606759176486912): i.e., kubernetes on it’s own is hard. As Ramji points out (https://www.youtube.com/watch?v=1HErHINvyIA), PKS means you’ll get a consistent, standardized kubernetes/container technology across the Dell Technologies portfolio. Watters lays it out (https://twitter.com/wattersjames/status/902571713057001472). Positioning: guidance seems to be that PKS is mostly for large organizations, “enterprises.” PKS to GA in 2017Q4, pricing then too. Diagram here (http://www.techrepublic.com/article/vmware-partners-with-pivotal-google-cloud-to-launch-kubernetes-based-container-service/):. Some vendor exec story-time here (http://social.techcrunch.com/2017/08/29/pivotal-vmware-google-partner-on-container-project/), and Pivotal blog post (https://content.pivotal.io/announcements/introducing-pivotal-container-service-pks-the-simple-way-to-bring-kubernetes-to-enterprise-customers). So, you can run PCF and PKS side-by-side (https://twitter.com/cloudnativeapps/status/903048428581560320). See longer explanation from Chad Sakac (http://virtualgeek.typepad.com/virtual_geek/2017/08/vmworld-2017-pivotal-container-services-pks.html): “historically, [Dell Technologies’] point of view on the container/cluster manager abstraction ecosystem wasn’t clear” https://d2mxuefqeaa7sj.cloudfront.net/s_57F3D537859409EDBA712760195C49AEF69FA177BC08164311E795F7016DE1F9_1504121396993_PCF+ERT+and+PKS.png See also this pro'er diagram (https://twitter.com/cote/status/903344343003664386). Lots of emphasize on a unified, compatible approach/GTM: “We now have a Cloud Native/Digital Transformation stack where there is a SINGLE target we are furiously running towards now as VMware, Pivotal, and Dell EMC – no mis-alignment, no differences in PoV. “ Market context: (https://cote.io/2017/06/02/451s-container-orchestration-usage-survey-notebook/) You may recall Coté’s summary of the CoreOS commissioned 451 survey (https://cote.io/2017/06/02/451s-container-orchestration-usage-survey-notebook/), which linked to a 2016(?) Gartner survey (https://www.gartner.com/document/3574617) where 18% of respondents had containers in production, with 4% being “significant production” That CoreOS/451 survey (https://cote.io/2017/06/02/451s-container-orchestration-usage-survey-notebook/) had a very important footnote: the survey respondents were already running containers already. It was more about which container orchestration platforms they liked. It was hard to do conclusive ranking of container orchestrators since people were using multiple ones. But, if you lump together CoreOS’s kubernetes distro with generic kubernetes, kubernetes wins out over Docker Swarm, 49% vs. 36%. Meanwhile (https://www.gartner.com/document/3782167): “By 2020, 50%+ of global enterprises will be running containerized applications in production, up from

In the last episode for 2016, Mark and Francesc look at all their favourite moments from this year, including their favourite episodes, guests and Cool Things of the Week. Cool thing of the week Google partners with Improbable to support next generation of video games blog Announcing new Google Cloud Client Libraries for four key services blog Kubernetes 1.5: Supporting Production Workloads blog Favourite Episodes Top Downloaded Episodes #46: Borg and Kubernetes with John Wilkes gcppodcast.com #44: Cloud Endpoints with Dan Ciruli and Sepehr Ebrahimzadeh gcppodcast.com #31: TensorFlow with Eli Bixby gcppodcast.com #37: GKE 1.3 with Carter Morgan gcppodcast.com #43: gRPC at CoreOS with Brandon Philips gcppodcast.com Mark's Favourites #19: GCP Next Speakers gcppodcast.com #23: Humble Bundle with Andy Oxfeld gcppodcast.com #52: Google Developer Experts Summit gcppodcast.com Francesc's Favourites #25: Go on the Cloud with Andrew Gerrand and Chris Broadfoot gcppodcast.com #38: Site Reliability Engineering with Paul Newson gcppodcast.com #43: gRPC at CoreOS with Brandon Philips gcppodcast.com Favourite Cool Things of the Week Francesc's Favourites Spotify is now on Google Cloud Platform: Spotify chooses Google Cloud Platform to power data infrastructure blog Announcing Spotify Infrastructure's Googley Future blog Google's BigQuery is da bomb - I can start with 2.2Billion ‘things' and compute/summarize down to 20K in < 1 min. tweet Kubernetes and Google Container Engine Kubernetes 1.3 on tap for Google Container Engine blog Google Container Engine now on Kubernetes 1.4 blog Bringing Pokémon GO to life on Google Cloud blog Education: CP100A: Google Cloud Platform Foundations courses New Google Cloud Platform Education Grants offer free credits to students blog Kubernetes class on Udacity blog Mark's Favourites Multiple General Availabilities Cloud SQL, Cloud Bigtable and Cloud Datastore are now generally available blog Cloud Router docs Cloud CDN docs Identity and Access Management (IAM) docs Machine Learning and Big Data How a Japanese cucumber farmer is using deep learning and TensorFlow blog Decoding the micro-moments of baseball: can you hear the game through data? blog Introducing Cloud Natural Language API, Speech API open beta and our West Coast region expansion blog Powering geospatial analysis: public geo datasets now on Google Cloud blog Introducing the Open Images Dataset blog Google Cloud Platform Community Slack Join the community invite We'll be back on January 18th, 2017 - See you all then!

Paul Newson is back to the podcast to tell us about his experience as an SRE, or Site Reliability Engineer. They keep Google and Google Cloud running and he explains to your cohosts Francesc and Mark how they make that happen. About Paul Paul currently is going through a six month rotation as a Software Reliability Engineer, previously he focused on helping developers harness the power of Google Cloud Platform to solve their big data problems. Before that, he was an engineer on Google Cloud Storage. Before joining Google, Paul founded a startup which was acquired by Microsoft, where he worked on DirectX, Xbox, Xbox Live, and Forza Motorsport, before spending time working on machine learning problems at Microsoft Research. Cool thing of the week Introducing Cloud Natural Language API, Speech API open beta and our West Coast region expansion blog Interview What is ‘Site Reliability Engineering'? Interview Google Cloud Platform opens its first West Coast region TechCrunch Site Reliability Engineering Book Go Programming Language Homepage Keys to SRE - SREcon14 YouTube Adventures in SRE-land: Welcome to Google Mission Control blog Question of the week How Kubernetes Updates Work on GKE blog Were will we be? Francesc is working on a video series justforfunc Mark will be at PAX DEV in Seattle and then Strange Loop in St Louis

Digital Marketing News #31 - Facebook Keyword Search, Web Speech API & More by YokoCo

In this episode of The Treehouse Show, Nick Pettit (@nickrp) and Jason Seifer (@jseifer) talk about the latest in web design, web development, html5, front end development, and more.

In this episode of The Treehouse Show, Nick Pettit (@nickrp) and Jason Seifer (@jseifer) talk about the latest in web design, web development, html5, front end development, and more.

Zu viert machten wir uns diese Woche auf in die Sendung. Mit von der Partie war als Gast Sebastian Golasch. Keine News Schaunotizen [00:00:25] Typecsset Harry Roberts beschreibt in seinem Artikel Single-direction margin declarations die Vorzüge, margins für Elemente nur in eine Richtung zu verwenden und entwickelt mit Typecsset die passende Library um vertikalen Rhythmus […]

Most people would agree that speech can be the ultimate input mechanism. Windows Phone demonstrated this: many of the first party experiences could be driven by speech in our first two releases. In WP8, we've made speech extensible, and given you the ability to leverage it a number of compelling ways within the context of your app. In this session, we'll show you everything you need to know.

Summary: About what I have been doing lately as well as my experiences with Microsoft's idea of speech recognition. Download MP3 (24:08 min, 14.2 MB) Show notes: The usual hickup with a crashing audition Are you still there? Useful Sounds has moved over to usefulsounds.com - please update your links as well as check your podcatcher. :) All podcasts entries have been moved over to this web page and all blog postings should be merged to cruel to be kind Redirecting the feed: Shoutouts to Podnova for handling of the feeds as it is supposed to be! Buuh for Odeo! I had to kill the old feed and am not able to transfer you, sorry. (Link to the new page on odeo.) Some comments on my recent trip to the States Steep streets in San Francisco (try of picture proof one and two) and touristy stuff The museum of modern art - nothing I can relate to The Vegas Style: "European" structures in San Jose Quiting my old job and some vacation in too warm Germany World Cup: unexpected flag explosion all over the place, my stay at the Coca-Cola flat and a new addiction to Coke Blak My failed experiments with English Speech Recognition testing especially the MS Speech Engine API why can't I train such an application with my own writing? What better way to train it with your own voice and style? I don't mind training an application - I know I don't fit into your saved profiles! But at least I am consistent in my speaking. stupid training lessons from Microsoft for voice training - who talks like H.G. Wells or Aesop? Portable Media Expo is coming! Yuuuuhuu! :o) :) :) Do not give up your audio podcast! Not everybody loves Video! A teaser for next episode: In a world of infinite choice, context - not content - is king. Claiming the Odeo Channel (odeo/97e6010dc9627079)