Podcasts about wavenet

MIPIM 2022 Highlights This is our Highlights of MIPIM episode, recorded onsite in the Propel by MIPIM area where numerous people from around the world stopped by the #WorkBold mobile podcast nook to share their BOLDEST prediction for the future of commercial real estate.  And what a diverse mix of ideas… We hope this episode inspires you to reflect and think about your own BOLD ideas.  We invite you to share your Bold predictions with Caleb on social media or DM.  To kick this episode off, Caleb shares his own BOLD prediction. Listen in to find out… Connect with Caleb on LinkedIn  If you have any questions or feedback on this episode, email podcast@workbold.co   Connect with our guests from this episode:  Dan Hughes, Alpha Property Insights, S1Ep4 Paul Unger, PlaceTech Richard Bertram, TSK Patryk Wakuła, SONTE Poland Freddy Marcos, rentbrella Caterina Maiolini, SALTO Systems Christian Schmitz, SALTO Systems Theresa Mueller, Trelleum Real Estate  Saminder (Sammy) Pahal, UK PropTech Association  Michael Clark, Wavenet   Timestamps: [03:30] Dan Hughes: Boldest Prediction for the Future of Commercial Real Estate Two predictions:  The future of the office is human driven. Putting technologies into buildings will bring benefits and problems.  [05:45] Paul Unger: Boldest Prediction for the Future of Commercial Real Estate We've seen a lot of the ideas from the consumer world come through into the business world, but we're really only just getting started with consumerization of the real estate business. [07:35] Paul Unger: How are you finding MIPIM? [08:45] Paul Unger: When you come to MIPIM as a media company, what opportunities are you looking for?  [10:05] Richard Bertram: Boldest Prediction for the Future of Commercial Real Estate  The ESG agenda is going to revitalise and radically change property within the commercial sector.  [11:25] Richard Bertram: How are you finding MIPIM? [11:45]  Richard Bertram: What opportunities are you looking for?  [14:05] Patryk Wakuła: How have you found MIPIM?  [14:35] Patryk Wakuła: Boldest Prediction for the Future of Commercial Real Estate The boldest prediction of commercial real estate is that it is going be very eco-friendly.  [16:15] Freddy Marcos: Boldest Prediction for the Future of Commercial Real Estate People will come back to the office.   Properties need to bring more amenities and make it more like home.  Buildings should be green.  [18:25] Caterina Maiolini: How have you found MIPIM?  [19:50] Caterina Maiolini: Boldest Prediction for the Future of Commercial Real Estate  Whatever is going to happen, we shouldn't lose the focus on community. Start with the user and design the journey around that.  [22:00] Christian Schmitz: How have you found MIPIM?  [22:50] Christian Schmitz: What opportunities are you looking for?  [25:20] Christian Schmitz: Boldest Prediction for the Future of Commercial Real Estate Real estate will boom a lot. In the next 2-3 years, we will be rethinking real estate.  [29:00] Theresa Mueller: How have you found MIPIM?  [30:35] Theresa Mueller: Boldest Prediction for the Future of Commercial Real Estate A lot is going to be on blockchain and we must be prepared for change, quickly.  [31:40] Saminder (Sammy) Pahal: How have you found MIPIM?  [32:10] Saminder (Sammy) Pahal: What opportunities are you looking for? [32:40] Saminder (Sammy) Pahal: Boldest Prediction for the Future of Commercial Real Estate The PropTechs will come out of the bunker.  [34:40] Michael Clark: How have you found MIPIM?  [35:00] Michael Clark: Boldest Prediction for the Future of Commercial Real Estate From a tech perspective, I believe everything is amalgamating traditional telecommunications and software, where it's been pretty much two completely separate entities.   Resources: Get TSK's weekly 'work made better' newsletter   Shout Outs: NorNorm National Association of Realtors  Illinois Realtors Louisa Dickins, LMRE   Sponsors: Headline Sponsor: TSK TSK creates inspiring workplaces for some of the world's biggest brands across the UK and Ireland, They've been working for 25 years to deliver the best employee experiences and the vision of their clients. Not only do they create great places to work, TSK share workplace content every week from the latest data to inspiring spaces they've designed and built. You can read their latest insights at www.tskgroup.co.uk or check out their LinkedIn and Instagram pages to become a follower, fan and friend. TSK publish weekly thought leadership, research and content featuring their team, clients and partners about workplace, commercial interiors, hybrid working and how others have prospered from investing in workplace. You can check their latest publications and video content in the show notes by signing up to their weekly ‘work made better' newsletter or visit tskgroup.co.uk.   Fortune Favours the Bold Bold merges property management & Space-as-a-Service to help office customers grow faster and drive asset value. Bold is a real estate brand owned and operated by NewFlex (www.workbold.co)    Future Proof Your Portfolio with NewFlex NewFlex delivers and manages a range of branded solutions for every type of building, in every type of location, for every type of occupier. Including the flexibility to develop your own brand. All enabled by flexible management contracts where we are invested in making money for you. (www.newflex.com)   Launch Your Own Podcast Kopus.com is the leading podcast production and strategic content company for brands, organisations, institutions, individuals, and entrepreneurs. Our team sets you up with the right strategy, equipment, training, and guidance and content to ensure you sound amazing while speaking to your niche audience and networking with your perfect clients. Get in touch jason@kopus.com (www.Kopus.com)

AI doesn't just exist in the lab, it's already solving a range of problems in the real world. In this episode, Hannah encounters a realistic recreation of her voice by WaveNet, the voice synthesising system that powers the Google Assistant and helps people with speech difficulties and illnesses regain their voices. Hannah also discovers how ‘deepfake' technology can be used to improve weather forecasting and how DeepMind researchers are collaborating with Liverpool Football Club, aiming to take sports to the next level. For questions or feedback on the series, message us on Twitter @DeepMind or email podcast@deepmind.com.  Interviewees: DeepMind's Demis Hassabis, Raia Hadsell, Karl Tuyls, Zach Gleicher & Jackson Broshear; Niall Robinson of the UK Met Office CreditsPresenter: Hannah FrySeries Producer: Dan HardoonProduction support: Jill AchinekuSounds design: Emma BarnabyMusic composition: Eleni ShawSound Engineer: Nigel AppletonEditor: David PrestCommissioned by DeepMind Thank you to everyone who made this season possible!  Further reading: A generative model for raw audio, DeepMind: https://deepmind.com/blog/article/wavenet-generative-model-raw-audioWaveNet case study, DeepMind: https://deepmind.com/research/case-studies/wavenetUsing WaveNet technology to reunite speech-impaired users with their original voices, DeepMind:| https://deepmind.com/blog/article/Using-WaveNet-technology-to-reunite-speech-impaired-users-with-their-original-voicesProject Euphonia, Google Research: https://sites.research.google/euphonia/about/Nowcasting the next hour of rain, DeepMind: https://deepmind.com/blog/article/nowcastingNow DeepMind is using AI to transform football, WIRED: https://www.wired.co.uk/article/deepmind-football-liverpool-aiAdvancing sports analytics through AI, DeepMind: https://deepmind.com/blog/article/advancing-sports-analytics-through-aiMetOffice, BBC: https://www.metoffice.gov.uk/The village ‘washed on to the map', BBC: https://www.bbc.co.uk/news/uk-england-cornwall-28523053Michael Fish got the storm of 1987 wrong, Sky News: https://news.sky.com/story/michael-fish-got-the-storm-of-1987-wrong-but-modern-supercomputers-may-have-missed-it-too-11076659#:~:text=In%20a%20lunchtime%20broadcast%20on,%2C%22%20he%20confidently%20told%20viewers.

On the 42nd episode of Zemach Fm, we are discussing about some well-known companies and implementations that are doing and have done a huge impact on the growth of Artificial intelligence. We will talk about how those companies and implementations achieved that, how the services are provided, what kind of projects and implementations they are composed of, and many more. Episode Timeline 02፡30 Introduction to the episode title 03:10 What is the AI Effect 05:30 Baidu – A company from china with advanced Artificial intelligence implementations 07:00 Baidu in the fight against Covid-19 using Artificial intelligence 08:40 Other AI implementations of Baidu 12:40 Deepmind – The AI powerhouse of Google 12:50 Alphafold from Deepmind. Structuring human proteins. 14:00 Alphago beating Go champions 16:30 Wavenet – Sound synthesis AI implementation from Deepmind. 18:35 Open AI progressing machine learning models 20:15 Models from Open AI 24:45 Watson service from IBM 26:30 The kind of knowledge that IBM Watson holds 29:30 Sophia the robot 30:00 Where Sophia got her looks from 31:10 What makes Sophia different from other Humanoids 34:00 What does Sophia being a Saudi Arabian citizen mean 40:13 Cimon the robot – helping astronauts in space. 42:12 WAYMO and self-driving cars Contact the hosts Henok Tsegaye Twitter Instagram LinkedIn Abdulhadmid Oumer Twitter Instagram linkedIn Follow Zemach FM and give us comment

Leva apenas 3,7 segundos de áudio para clonar uma voz. Esta façanha impressionante, e preocupante, foi anunciada pela chinesa Baidu, uma das maiores empresas de tecnologia do mundo. Um ano atrás, a ferramenta de clonagem de voz da empresa chamada Deep Voice exigia 30 minutos de áudio para fazer o mesmo. Isso mostra o quão rápido a tecnologia para criar vozes artificiais está se acelerando. Em pouco tempo, os recursos de geração de voz de Inteligência Artificial se expandiram e se tornaram mais realistas, o que torna fácil o uso indevido da tecnologia. Como todos os algoritmos de inteligência artificial, quanto mais dados as ferramentas de clonagem como Deep Voice receberem para treinar, mais realistas vão ser os resultados. Recentemente, o Google revelou o Tacotron 2, um sistema de conversão de texto em fala, e o método de geração de voz WaveNet. O WaveNet analisa uma representação visual de áudio, chamada espectrograma. Esse sistema gera o áudio. Ele é usado para gerar a voz para o Google Assistente. Esta tecnologia é tão realista que é quase impossível dizer o que é gerado por IA e qual voz é gerada por humanos. O algoritmo aprendeu como pronunciar palavras e nomes desafiadores que seriam um sinal revelador de uma máquina, bem como enunciar palavras com mais naturalidade. Essa tecnologia avançada abre as portas para empresas fornecerem novos serviços e produtos. A Lyrebird, por exemplo, usa inteligência artificial para criar vozes para chatbots, audiolivros, videogames, leitores de texto e muito mais. Eles reconhecem em seu site que “com uma grande inovação vem uma grande responsabilidade”, ressaltando a importância dos pioneiros dessa tecnologia tomarem muito cuidado para evitar o uso indevido da tecnologia. Semelhante a outras novas tecnologias, a voz artificial pode ter muitos benefícios, mas também pode ser usada para enganar indivíduos. À medida que os algoritmos de IA ficam melhores e fica difícil discernir o que é real e o que é artificial, haverá mais oportunidades de usá-los para fabricar a verdade. De acordo com pesquisas, nossos cérebros não registram diferenças significativas entre vozes reais e artificiais. Na verdade, é mais difícil para nosso cérebro distinguir vozes falsas do que detectar imagens falsas. Agora que esses sistemas de inteligência artificial requerem apenas uma pequena quantidade de áudio para criar uma voz artificial que imite o estilo de fala e o tom de um indivíduo, a oportunidade de abuso aumenta. Até agora, os pesquisadores não foram capazes de identificar uma distinção neural de como um cérebro pode distinguir entre o real e o falso. Imagine como vozes artificiais poderiam ser usadas em uma entrevista, notícias ou conferência de imprensa para fazer os ouvintes acreditarem que estão ouvindo uma figura de autoridade no governo ou um CEO de uma empresa. Aumentar a conhecimento sobre essa tecnologia e como ela funciona é o primeiro passo para evitar que os ouvintes acreditem em vozes artificiais quando elas são usadas para nos enganar. O principal receio é que as pessoas possam ser enganadas se agirem com base em algo falso porque parece que vem de alguém real. Algumas pessoas estão tentando encontrar uma solução técnica para nos proteger. No entanto, uma solução técnica não será 100% infalível. Nossa capacidade de avaliar criticamente uma situação, avaliar a fonte de informação e verificar sua validade se tornará cada vez mais importante.

Deepfake voice technology based on voice cloning, or quasi-perfect reproductions of a person’s voice, can be used both for the good and for the bad. It can be put in the service of voice synthesis that can give a voice back to people who would otherwise lose it due to acute or chronic conditions such as ALS, apraxia, traumatic brain injury, stroke, etc.It is already being used in the film and TV industry, gaming, call centers, and it is also potentially convenient for encryption and therapy. However, there is no denying that it can pose a significant threat to democratic processes, particularly to those related to the value of privacy. If used inappropriately, deep-fake voice technology can perpetuate deceit and harassment.Precisely because we are fully aware of this, we at Respeecher place a great deal of emphasis on the use of voice technology in ways that minimize the risk of fooling people into thinking someone said something they didn't.We are committed to ensuring that our groundbreaking technology is only used for ethical projects, and does not fall into the wrong hands. We do not use the voice of a private person or an actor without permission, and we always ask for voice owners’ written consent. However, we do allow non-deceptive use of the voices of historical figures and politicians, such as Richard Nixon or Barack Obama, but only for projects that meet ethical standards.What about use cases for businesses? Numbers show that there is a huge opportunity for economic organizations to leverage voice to acquire and retain new business. According to an AppDynamics report from 2018, half the web searches were forecasted to be voice-driven by 2020.61% of the surveyed IT decision-makers take this even further, expecting that voice commands would completely replace manually typed commands for finding information on the Internet. And the young generation leads the way - 84% of millennials already use voice assistants to help them keep track of their daily schedule and responsibilities.The Good.Giving the ability to speak naturally back to people who suffer from a wide range of medical conditionsThe ability to communicate, sharing thoughts and feelings by uttering words is extremely important, in fact, it is among those things that make us, humans, special. But there is more to what groundbreaking voice conversion technology can do for vocally impaired people.Consider the expansion of home automation technologies with vocal control. Voice cloning could make people who can’t speak naturally more independent, better able to make use of the devices that can be vocally commanded.Voice assistantsAccording to Ovum's Digital Assistant and Voice AI–Capable Device Forecast: 2016–21, by 2021 voice assistants will outnumber the human beings that live on Earth. Let’s take Google Assistant as an example. Its voice is generated by the text-to-speech system Tacotron 2, based on two deep neural networks.The first transforms the text into a visual representation (i.e., the spectrogram) of audio frequencies over time, and then a WaveNet system analyses the spectrogram and creates audio elements. The outcome is speech that is nearly indistinguishable from human speech, even when it comes to the pronunciation of challenging words.Interactive content for online learning coursesVoice cloning with artificial intelligence makes it unnecessary to record notes for every new session, or to record again in order to correct potential mistakes. This leads to the reduction of both financial and time costs of professionally recorded lectures, and hence it fosters the proliferation of online courses. And this is no small thing, particularly during the tough times that we are traversing due to COVID-19 restrictions.The BadBlackmailFake, yet extremely realistic, videos with explicit sexual or violent scenes may be created by joint usage of deepfake voice technology and deepfake video.Spam emailsIf you’ve received an email asking you to “contact bank X via the below email to guide you further on the wire transfer procedure”, it’s quite likely that you regard it as spam and do nothing about it. However, a subsequent phone call from somebody who sounds exactly like a trusted contact, advising you to respond to the email, might change your mind and make you do something you will have wished you hadn’t.Serving unlawful competitionSomeone may pretend to be the CEO of company X, and from this position present sham data during fake earnings calls, fooling stakeholders and investors into believing that stock prices are different from what they really are. The same illicit technique can be used to sabotage industry rivals.We are painfully aware that synthetic media technology can potentially be used in harmful ways. This is one of the reasons why our tech is not accessible to the public. We restrict usage of our voice conversion systems to non-deceptive content creation applications, by limiting who we work with and what we allow them to do with our technology.We hope that being early to market, we can actually help educate the public about what is technically possible and make people less likely to fall for deceptive synthetic speech. We also think that an important role in limiting this harm can be played by gatekeepers such as Youtube and Facebook, and we are ready to work with such platforms to detect and prominently label synthetic speech.The FutureB2B use casesGiven the findings of the above-cited AppDynamics report, the use of voice conversion technology by companies should be framed not in terms of if, but of when. 69% of the IT decision-makers work for organizations that already invest in, or plan to invest in voice technology during the next 3 years.Whether you’re looking at voice replication, therapy for speech problems, dubbing and ADR, encryption, gaming, etc., all of these are likely to benefit from leveraging voice cloning. The envisaged development of a real-time system (currently an ongoing process) within gaming, for instance, will allow players to use different voices in in-game chats. Things are evolving fast when it comes to deepfake voice technology.Voice cloning for call centersRespeecher is now working on breakthrough technologies that will make overseas operators able to sound like locals. At long last, we are getting closer to the solution for getting operators to sound more like the people they are speaking with over the phone. Along the same lines, our robotic operators will soon sound more human once we get the voice makeover “up and running”.ConclusionDeepfake voice technology does indeed pose security risks, but acknowledging them and trying to minimize them are the first steps towards focusing mainly on the good. Cloned voices that sound indistinguishable from the original speakers are a match made in heaven for filmmakers, game developers, other media content creators, and soon, also for call centers.Since digitally replicated voices can already capture nuances and emotions, the scope of application areas is enlarging, as it may be obvious for all of you who have recently tried to talk to (yes, the phrase is correct!) virtual assistants such as Samsung's Bixby, Apple's Siri or Amazon's Alexa.Counseling and companionship are the new functions that are expected to emerge from generating voices that express emotions. The creative process will be streamlined by the newly acquired possibility to change content without the need to re-record original voices.This article does not necessarily reflect the opinions of the editors or management of EconoTimes.Source: econotimes.com.

In this episode of Intel on AI guest Colin Murdoch, Senior Business Director at DeepMind, talks with host Abigail Hing Wen, Intel AI Tech Evangelist and New York Times best-selling author, about text-to-speech system WaveNet, the recent breakthrough with AlphaFold, the potential for artificial intelligence to solve energy challenges, and how Google adopts cutting-edge research […]

In this episode of Intel on AI guest Colin Murdoch, Senior Business Director at DeepMind, talks with host Abigail Hing Wen, Intel AI Tech Evangelist and New York Times best-selling author, about text-to-speech system WaveNet, the recent breakthrough with AlphaFold, the potential for artificial intelligence to solve energy challenges, and how Google adopts cutting-edge research into a number of services. The two also discuss examples like AlphaGo, GraphNet, advancements in Android products, and what the future of artificial general intelligence might look like. Follow DeepMind on Twitter: twitter.com/DeepMind Follow Abigail on Twitter: twitter.com/abigailhingwen Learn more about Intel’s work in AI: intel.com/ai

In this episode of Intel on AI guest Colin Murdoch, Senior Business Director at DeepMind, talks with host Abigail Hing Wen, Intel AI Tech Evangelist and New York Times best-selling author, about text-to-speech system WaveNet, the recent breakthrough with AlphaFold, the potential for artificial intelligence to solve energy challenges, and how Google adopts cutting-edge research into a number of services. The two also discuss examples like AlphaGo, GraphNet, advancements in Android products, and what the future of artificial general intelligence might look like. Follow DeepMind on Twitter: twitter.com/DeepMind Follow Abigail on Twitter: twitter.com/abigailhingwen Learn more about Intel’s work in AI: intel.com/ai

Andreas Jansson is the co-founder of Replicate, a version control tool for machine learning. He holds a PhD from City University of London in Music Informatics and was previously a machine learning engineer at Spotify, researching and applying algorithms for music information retrieval. Learn more about Andreas: https://replicate.ai/ (https://replicate.ai/) https://www.linkedin.com/in/janssonandreas/ (https://www.linkedin.com/in/janssonandreas/) Every Thursday I send out the most useful things I've learned, curated specifically for the busy machine learning engineer. Sign up here: http://bitly.com/mle-newsletter (http://bitly.com/mle-newsletter) Follow Charlie on Twitter: https://twitter.com/CharlieYouAI (https://twitter.com/CharlieYouAI) Subscribe to ML Engineered: https://mlengineered.com/listen (https://mlengineered.com/listen) Comments? Questions? Submit them here: http://bit.ly/mle-survey (http://bit.ly/mle-survey) Take the Giving What We Can Pledge: https://www.givingwhatwecan.org/ (https://www.givingwhatwecan.org/) Timestamps: 02:30 Andreas Jansson 07:30 Overview of music information retrieval (MIR) 13:30 Why use spectrograms and not raw audio? 19:55 The potential for transformers in MIR 22:45 Most exciting applications for ML in MIR 29:20 Challenges in putting ML into production 36:45 What Andreas imagines for the future of ML tools 41:45 Why he's building a tool for ML version control (http://replicate.ai/ (http://replicate.ai/)) 52:55 What Replicate enables via integration or as a platform 01:02:55 Learnings from doing customer discovery for Replicate 01:14:10 "Github for ML models and data" 01:22:30 Rapid fire questions Links: https://deepmind.com/blog/article/wavenet-generative-model-raw-audio (WaveNet: a generative model for raw audio) https://openaccess.city.ac.uk/id/eprint/19289/1/ (Singing Voice Separation with Deep U-Net CNNs) https://openaccess.city.ac.uk/id/eprint/23669/1/ (Joint Singing Voice Separation and F0 Estimation with Deep U-Net Architectures) https://www.arxiv-vanity.com/ (arXiv Vanity) https://replicate.ai/ (Replicate) https://discord.gg/QmzJApGjyE (Replicate's Discord)

Google Text-To-Speech translates text into spoken word. In this post, we'll teach you how to use Google Text-to-Speech and its human-like WaveNet voices to improve the accessibility of your blog posts. You don't need to be a software developer to follow our guide.

Today on the podcast, we speak with Ian Buck and Kari Briski of NVIDIA about new updates and achievements in deep learning. Ian begins by telling hosts Jon and Mark about his first project at NVIDIA, CUDA, and how it has helped expand and pave the way for future projects in super computing, AI, and gaming. CUDA is used extensively in computer vision, speech and audio applications, and machine comprehension, Kari elaborates. NVIDIA recently announced their new Tensor Cores, which maximize their GPUs and make it easier for users to achieve peak performance. Working with the Tensor Cores, TensorFlow AMP is an acceleration into the TensorFlow Framework. It automatically makes the right choices for neural networks and maximizes performance, while still maintaining accuracy, with only a two line change in Tensor Flow script. Just last year, NVIDIA announced their T4 GPU with Google Cloud Platform. This product is designed for inferences, the other side of AI. Because AI is becoming so advanced, complicated, and fast, the GPUs on the inference side have to be able to handle the workload and produce inferences just as quickly. T4 and Google Cloud accomplish this together. Along with T4, NVIDIA has introduced TensorRT, a software framework for AI inference that’s integrated into TensorFlow. Ian Buck Ian Buck is general manager and vice president of Accelerated Computing at NVIDIA. He is responsible for the company’s worldwide datacenter business, including server GPUs and the enabling NVIDIA computing software for AI and HPC used by millions of developers, researchers and scientists. Buck joined NVIDIA in 2004 after completing his PhD in computer science from Stanford University, where he was development lead for Brook, the forerunner to generalized computing on GPUs. He is also the creator of CUDA, which has become the world’s leading platform for accelerated parallel computing. Buck has testified before the U.S. Congress on artificial intelligence and has advised the White House on the topic. Buck also received a BSE degree in computer science from Princeton University. Kari Briski Kari Briski is a Senior Director of Accelerated Computing Software Product Management at NVIDIA. Her talents and interests include Deep Learning, Accelerated Computing, Design Thinking, and supporting women in technology. Kari is also a huge Steelers fan. Cool things of the week Kubernetes 1.14: Production-level support for Windows Nodes, Kubectl Updates, Persistent Local Volumes GA blog Stadia blog How Google Cloud helped Multiplay power a record-breaking Apex Legends launch blog Massive Entertainment hosts Tom Clancy’s The Division 2 on Google Cloud Platform blog Interview NVIDIA site NVIDIA Catalog site CUDA site Tensor Cores site TensorFlow sote Automatic Mixed Precision for Deep Learning site Automatic Mixed Precision for NVIDIA Tensor Core Architecture in TensorFlow blog TensorFlow 2.0 on NVIDIA GPU video NVIDIA Volta site NVIDIA T4 site WaveNet blog BERT blog Compute Engine site T4 on GCP site Webinar On Demand: Accelerate Your AI Models with Automatic Mixed-Precision Training in PyTorch site PyTorch site NVIDIA TensorRT site TensorRT 5.1 site Kubernetes site Rapids site NVIDIA GTC site Deep Learning Institute site KubeFlow Pipeline Docs site KubeFlow Pipelines on GitHub site NVIDIA RTX site Question of the week Where can we learn more about Stadia? general info developer access Where can you find us next? Mark will be at Cloud NEXT, ECGC, and IO. Jon may be going to Unite Shanghai and will definitely be at Cloud NEXT, ECGC, and IO. NVIDIA will be at Cloud NEXT and KubeCon, as well as International Conference on Machine Learning, The International Conference on Learning Representations, and CVPR

Can you tell the difference between computer-generated voices vs. human voices? Voice used to be a human attribute. Not anymore! AI can duplicate virtually any voice, including your own. Join Kim Komando and learn more about this life-changing technology taking over soon in this Komando on Demand podcast.

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Revisando los enlaces con Herramienta SEO https://www.borjagiron.com/seo/mejores-herramientas-seo/ (Metricspot, XOVI...) 3. Revisando el robots.txt que no cambie 4. Añadiendo alertas en GA y uptimerobots 5. Usando plantillas y plugins comprados y todo siempre actualizado 6. Buen servidor Cómo solucionar un ataque de SEO Negativo 1. Si es por enlaces de baja calidad: Mandar un disavow a Google para decir a Google que enlaces no tenga en cuenta (Ver herramientas SEO) 2. Si es robots cambiar contraseña y actualizarlo 3. Cambiando la plantilla y desinstalando plugins. Instalación de cero e importar contenidos... 4. Cambiando de servidor. Hablando con el soporte. Cada vez es más dificil ya que Google no tiene en cuenta casos puntuales siempre que se solucionen de una forma rápida. 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Soy Vilma Núñez y puedo ayudarte - Noticia de la semana: https://searchengineland.com/new-search-quality-raters-guidelines-google-assistant-voice-search-evaluations-289114 La nueva calidad de búsqueda califica las pautas para el Asistente de Google y las evaluaciones de búsqueda por voz Google tiene evaluadores de calidad específicamente para resultados de búsqueda relacionados con la búsqueda por voz. Estos evaluadores buscan información, satisfacción, duración, formulación y elocución. Google ha publicado en el blog de Google Research las directrices de calificadores de calidad de búsqueda , directrices de los contratistas para evaluar los resultados de búsqueda de Google, específicamente para el Asistente de Google y los resultados de búsqueda por voz. Es similar a las pautas de calidad de búsqueda web, pero cambia en cuanto a que no hay una pantalla que observar al evaluar dichos resultados; en su lugar, está evaluando las respuestas de voz del Asistente de Google. Google explicó: "El Asistente de Google necesita sus propias pautas, ya que muchas de sus interacciones utilizan lo que se llama 'tecnología sin ojos' cuando no hay pantalla como parte de la experiencia". Google ha diseñado algoritmos y aprendizaje automático para intente hacer que las respuestas de voz y las "respuestas sean gramaticales, fluidas y concisas". Google dijo que le piden a los evaluadores que se aseguren de que las respuestas sean satisfactorias en varias dimensiones: Satisfacción con la información: el contenido de la respuesta debe cumplir con las necesidades de información del usuario. Longitud: cuando una respuesta mostrada es demasiado larga, los usuarios pueden escanearla visualmente y localizar la información relevante. Para las respuestas de voz, eso no es posible. Es mucho más importante garantizar que proporcionamos una cantidad útil de información, con suerte no demasiado o muy poco. Algunos de nuestros trabajos previos se usan actualmente para identificar los fragmentos de respuestas más relevantes. Formulación: es mucho más fácil entender una respuesta escrita mal formulada que una respuesta no gramatical, por lo que se debe tener más cuidado para garantizar la corrección gramatical. Elocución: las respuestas verbales deben tener una pronunciación adecuada y prosodia. Las mejoras en la generación de texto a voz, como WaveNet y Tacotron 2 , están reduciendo rápidamente la brecha con el rendimiento humano. 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Paweł Cyrta zajmuje się uczeniem maszynowym już kawał czasu. Ale ciekawostka jest taka, że zajmuje się głównie dźwiękiem i tematami powiązanymi, takimi jak synteza mowy lub brand sound design. Między innymi, rozmawialiśmy o sieci neuronowej WaveNet, co ciekawe w międzyczasie wyszła nowa wersja sieci, która jest jeszcze bardziej sprawna. Jak szybko ten świat rozwija się. Zapraszam do wysłuchania.http://biznesmysli.pl/20

Paweł Cyrta zajmuje się uczeniem maszynowym już kawał czasu. Ale ciekawostka jest taka, że zajmuje się głównie dźwiękiem i tematami powiązanymi, takimi jak synteza mowy lub brand sound design. Między innymi, rozmawialiśmy o sieci neuronowej WaveNet, co ciekawe w międzyczasie wyszła nowa wersja sieci, która jest jeszcze bardziej sprawna. Jak szybko ten świat rozwija się. Zapraszam do wysłuchania.http://biznesmysli.pl/20

Soutenez Tech Café sur Tipeee ou sur Patreon ! Lire le transcript (beta) Google tout Pixelisé (1'50) Les Pixels 2 et XL : superphones ultimes ou amuse gueules avant le Galaxy X ? Après le courage, le foutage de gueule ? De toutes façons, ils ne seront pas dispo en France... L’Assistant intégrera Lens et Wavenet. Le Chromebook Pixel. Les Pixel Buds. Avec assistant et traducteur intégré. Comme skype translator. Et les Pixels sont respectueux de votre concentration en voiture... Comme les capotes, les Google home se déclinent en toutes les tailles. Le pixel camera Clips : votre futur mouchard photographe personnel ? Et dans le reste de votre vie ? La dystopie du smartphone est-elle déjà en marche ? Pocketpoints Maillon Faible (1h 03') ICO prend plus rien… Sommes nous dans une blockchain bubble ? Bitcoin Cash, Filecoin, Singularitynet, Sexservice, la blockchain à toutes les sauces. Nouveaux mot/maux : le cryptojacking, Showtime aussi mine dans votre dos. Concours de teubés : les QI de Siri, Bing, Baidu et Assistant comparés. Un robot passe les examens des universités japonaise. Inquiétant. Pour les humains. Google lance son comité d’éthique sur l’IA En Bref… (1h 21') Le point sur la consommation réseau mobile en France On fait le point aussi sur la consommation d’apps Le projet de loi a évolué : il n’est plus question de livrer ses identifiants Et maintenant, les bijoux connectés. Windows Mobile est mort… wabon ? Apple, ça gonfle... OK Medor : Sony revient avec un Aibo connecté. Après le DEX, le DEX Book. Atrix, si tu nous regardes, repose en paix. L’Atari Box se dévoile mais reste un mystère… Après le Qi, le Pi. Bonus (1h 39') GPP : The circle. Guillaume : géocaching. Participants : Guillaume Poggiaspalla Présenté par Guillaume Vendé

In this episode of Device Squad, the podcast for the Mobile Enterprise from Propelics, Steve gets futuristic with MERL Senior Principal Research Scientist, John Hershey. The conversation centers around the current state of Neural Networks and artificial intelligence as John brings us the news from the recent NIPS (Neural Information Processing) conference in Barcelona.  We discuss voice recognition and replication strategies and what role they'll play in our everyday lives—along with John's current project, deep learning for signal separation, speech recognition, language processing, and multi-modal semantic representation learning. In other words, John has solved the problem of isolating a single voice in a crowd, a process known as Deep Clustering. Specifically, we discuss: the Universe Project - a software platform for measuring and training an AI's general intelligence across the world's supply of games, websites and other applications. WaveNet - a deep generative model of raw audio waveforms - able to generate speech which mimics human voice and sounds more natural than the best text-to-speech systems. Google's DeepDreams - DeepDream is a computer vision program created by Google which uses a convolutional neural network to find and enhance patterns in images via algorithmic pareidolia, thus creating a dreamlike hallucinogenic appearance in the deliberately over-processed images. MERL Deep Clustering - Training deep discriminative embeddings to solve the cocktail party problem.The human auditory system gives us the extraordinary ability to converse in the midst of a noisy throng of party goers. Solving this so-called cocktail party problem has proven extremely challenging for computers, and separating and recognizing speech in such conditions has been the holy grail of speech processing for more than 50 years. Deep clustering is a recently introduced deep learning architecture that uses discriminatively trained embeddings as the basis for clustering, producing unprecedented speaker-independent single-channel separation performance on two-speaker and three-speaker mixtures. John also predicts when our robot overlords will finally take over, and whether or not the revolution will take the form of an army of seemingly benevolent toys. Also, how long it will be before Alexa (and other) voice-controlled devices begin targeting content based on our emotional states.  Lastly, our two heroes engage in an exciting game of BLIP. Tune in and find out what this 1970's TOMY game has to do with with artificial intelligence and analog processing!  It's a long episode but a great one so be sure to tune in! Oh, and by the way, Mind Flex is a scam.

The O’Reilly Bots Podcast: A universal bot for messaging, mobile voice, and the home.In this episode of the O’Reilly Bots Podcast, Pete Skomoroch and I speak with Brad Abrams, group product manager of Google Assistant, the company’s new AI-driven bot that lives in many different contexts, including the Pixel phone, the Allo messaging app, and the Google Home voice-controlled speaker.Discussion points: “Actions,” Google’s API for Assistant plug-ins. These are available for Google Home now, and will be rolled out for other instances of Assistant later. The relationship between Assistant and Google’s Pixel phone. Google’s plans for the recently acquired API.ai, and where it fits in with Assistant. Google’s WaveNet technology, a text-to-voice engine that uses neural networks. Google’s voice user interface design guidelines, and how Google uses different voices in different settings.

The O’Reilly Bots Podcast: A universal bot for messaging, mobile voice, and the home.In this episode of the O’Reilly Bots Podcast, Pete Skomoroch and I speak with Brad Abrams, group product manager of Google Assistant, the company’s new AI-driven bot that lives in many different contexts, including the Pixel phone, the Allo messaging app, and the Google Home voice-controlled speaker.Discussion points: “Actions,” Google’s API for Assistant plug-ins. These are available for Google Home now, and will be rolled out for other instances of Assistant later. The relationship between Assistant and Google’s Pixel phone. Google’s plans for the recently acquired API.ai, and where it fits in with Assistant. Google’s WaveNet technology, a text-to-voice engine that uses neural networks. Google’s voice user interface design guidelines, and how Google uses different voices in different settings.

Evolutionary Leap INTRO Hello and welcome to Terrifying Robot Dog! I'm Jonathan Stark - and I'm Kelli Shaver - and we are here to talk about how technology is changing the way we interact with the world. This week we talk about talking machines. Please stay tuned, Terrifying Robot Dog is next... LINKS DeepDream WaveNet: A Generative Model for Raw Audio A melody written by a crowd Clive Thompson on Why Sci-Fi Is the Last Bastion of Philosophical Writing The bit where Jon and I talked about the necessary fidelity of generated audio vs. images reminded me of this -- ks Cochlear implant: simulation on speech and music TITLES Nightmare Creatures Comedy AI Evolutionary Leap CLOSING That's our show for this week. I'm Jonathan Stark - and I'm Kelli Shaver - and we hope you join us again next week for Terrifying Robot Dog. Bye! POST-SHOW Would you like to support Terrifying Robot Dog? Just think of two friends who would dig the show and send them to terrifyingrobotdog.com for links to iTunes, Facebook, and RSS feeds. If you don't have two friends, you can still help us out by leaving a nice review in iTunes. Thanks!