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AI and Machine Learning

Introduce efficiencies to improve operations and add intelligence for digital transformation of products or services.

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Introducing the AI & ML Moderators

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iliasC2C Team Member

published in AI and Machine Learning

Introducing the AI & ML Moderators

Let us introduce you to our AI & ML Moderator: Markus KoyUsername: markuskBio:Markus is the founder of thefluent.me and a Google Build Partner and AI enthusiast based in Vancouver, British Columbia. Markus has 18 years of experience as a Business Analyst, IT Project Manager, IT Consultant, Strategic Controller, and Developer. Born and raised in Germany, Markus immigrated to Canada in 2008. His hobbies include fishing, snowshoeing, and hiking. Fine out more about Markus and thefluent.me here: https://community.c2cglobal.com/product-updates/using-ai-to-improve-spoken-language-fluency-with-markus-koy-founder-of-thefluent-me-1628Company: thefluent.meJob Title: Founder/ Owner Mohammad AlaminUsername: malamin Bio:Mohammad is an AI/ML solutions architect at Aiiotsys. A computer training center has opened in Bangladesh. He was teaching computer skills to everyone. He graduated with honors in Computer Science from the University of Greenwich in London.Company: Aiiotsys.Job Titl

malaminModerator

posted in AI and Machine Learning

What is Document AI Workbench?

Holt Skinner, Google Developer Advocate discussed about Document AI Specialized processors and how they can provide intelligent insights into certain document types. However, what if you have a unique type of document and you're not getting the accuracy you need from a pre-trained processor? In this video, Holt Skinner dives into Document AI Workbench and explains how it allows you to create custom processors and uptrain existing specialized processors.Click on the video below to watch it in detail. Chapters:0:00 - Intro0:52 - What is Document AI Workbench?1:14 - What is uptraining?1:50 - What are Custom Processors?2:03 - Uptraining demo2:47 - Custom Processor demo3:08 - Model development workflow3:15 - Cloud Console Tutorial5:17 - Wrap up Extra Credit:Uptraining guide→ https://goo.gle/3EQHqVC Custom processors guide → https://goo.gle/3GJver0 Document AI Overview → https://goo.gle/3Gw4uud Document AI Training & Evaluation Overview → https://goo.gle/3tMxTZB The Future of Documents

MoamenNew to the Community

posted in AI and Machine Learning

AI

Is there a dark side in artificial intelligence? Especially on one side (artificial general intelligence) as they say

MarkusKModerator

posted in AI and Machine Learning

Would you want a robot as CEO?

NetDragon Websoft, the Chinese gaming company worth $10 billion, has recently appointed an AI-powered virtual humanoid robot named Tang Yu as the rotating CEO of its flagship subsidiary Fujian NetDragon Websoft.The company said the humanoid robot would “streamline process flow, enhance the quality of work tasks, and improve the speed of execution.” Tang Yu will also operate as “a real-time data hub and analytical tool to support rational decision-making in daily operations and enable a more effective risk management system.”What do you think? Here is the link to the article: https://www.euronews.com/next/2022/11/20/would-you-want-a-robot-as-ceo-chinese-firm-is-first-to-try-as-it-bets-on-metaverse-workpla

InAppChatNew to the Community

posted in AI and Machine Learning

Orchestrating DialogFlow alongside Amazon Lex and IBM Watson Assistant

1ChatBot from InAppChat.io now has the capability of integrating multiple NLU engines into a single platform to federate Bots from separate providers into a single chat interface. Does anyone have any use cases whereas they’ve been using DialogFlow but would like to add separate intents from other NLU providers to their Bot Stack? Article - https://bit.ly/3FG2Fu5Video - https://bit.ly/3DvQcXdBrochure - https://bit.ly/3fS1PQBPress Release - http://bit.ly/3Ap0Iio

Abhishek111Foundational Platinum Partner

asked in AI and Machine Learning

Input Text capped to maximum 2500 characters

Hi,In Vertex AI Jupyter Notebook while trying to do online prediction on my Pytorch model deployed on Vertex endpoint for a Text classification use case , I am getting below error - ServiceUnavailable: 503 502:Bad GatewayI have found there seems to be a limit on the text character and it’s capped to 2500 characters. Please correct me if I am wrong in this. While I am getting output for Input length less than 2500 characters, but for any input more than that I am getting the above error. Please help.

malaminModerator

posted in AI and Machine Learning

Revolutionise patient experience with the best of Google’s AI

Discover how Contact Center AI helps Life Sciences companies provide rich, lifelike, and seamless experiences for patients, and see a real life use case on how a Global Life Sciences company is transforming patient experience with Google’s AI technology.Join this event on November 29!Register here: https://cloudonair.withgoogle.com/events/emea-contact-center-ai

malaminModerator

posted in AI and Machine Learning

Integrating speech technology into your application with the STT API

Automatic speech recognition (ASR) can unlock new functionality for your customers and clients, but to get the most out of it, you have to optimize it to your use case. This session will cover how to optimize for different types of user-generated content — including voice media control and captioning —and how you can leverage our API to bring the power of voice engagement to your products and applications with multi-lingual, domain-specific models. Date: December 13, 2022 6:00 PM-6:30 PM GMT Click on the link below to join this event. https://cloudonair.withgoogle.com/events/innovators-integrating-speech-technology

malaminModerator

posted in AI and Machine Learning

Get seven days advance notice with forecast alerts

Alisa Goldstein, Senior Product Manager, Cloud Alerting and John Brier, Group Product Manager, Cloud Operations Suite will speak about Transition your operations management from reactive to proactive with forecasting from Google Cloud Alerting. Join this event to learn how you can set notifications for up to 7 days with advanced notification so you can act before a problem occurs. Date: December 13, 2022 5:00 PM- 5:30 PM GMT Click on the link below to join this event. https://cloudonair.withgoogle.com/events/innovators-forecast-alerts

malaminModerator

posted in AI and Machine Learning

Detecting fraud with Cloud Bigtable

With millions of daily credit card purchases, how can you detect which transactions are fraudulent before they complete? In this video, developer advocate Billy Jacobson shows how we can use big data processing tools, machine learning, and the scalable Bigtable database to detect fraud in milliseconds. Watch to learn how you can deploy your own fraud detection system with horizontal scalability!Click on the video below to watch it in detailChapters:0:00 - Intro0:29 - Transaction pipeline1:11 - Managing the stream of customer transactions1:41 - Cloud Pub/Sub integration with Cloud Dataflow3:01 - Pub/Sub output stream3:30 - Summary3:58 - Wrap up Credit card fraud detection using Cloud Bigtable → https://goo.gle/3tlX6toSubscribe to Google Cloud Tech → https://goo.gle/GoogleCloudTech

malaminModerator

posted in AI and Machine Learning

How to create ML models that teach themselves

Did you ever think about how self-driving cars work?How do ML and AI make decisions themselves without human touch?How ML and AI make decisions themself without human touch. One of the biggest challenges is training ML models with appropriate data sets, but what if the ML models could teach themselves? In this episode of Architecting with Google Cloud, Debi Cabrera, Google Cloud developer Advocate chat with Harrison at Helm.ai about how they help companies scale their capabilities with ML models.Check out this video so the next time you see a self-driving car you’ll know what’s happening under the hood! Click on the below to watch it in detail. Chapter0:00 - Intro0:48 - Helm.ai overview1:37 - Supervised vs unsupervised learning (deep teaching)3:24 - Real-world example of unsupervised learning4:50 - Can the software be used on more than cars?5:47 - Helm.ai architecture12:14 - Future technical enhancements14:18 - Wrap Up Architecting with Google Cloud playlist → https://goo.gle/Architect

malaminModerator

posted in AI and Machine Learning

Best Practices for managing Vertex Pipelines code

Machine learning pipelines are increasingly being used by organizations to streamline and scale their ML workflows. However, managing these pipelines can be difficult when an organization has multiple ML projects and pipelines in various stages of development. To address this, Google cloud developer advocates suggested that a method be developed to build on DevOps concepts and apply them to this ML-specific problem.In this post, Google Cloud developer advocates share some best practices for managing the codebase for your ML pipelines based on their work with top Google Cloud customers and partners.Click on the link below to read it in detail:https://cloud.google.com/blog/topics/developers-practitioners/best-practices-managing-vertex-pipelines-code

malaminModerator

posted in AI and Machine Learning

Unlock Innovation with Google’s Data Cloud

Every organisations face three key challenges when it comes to unlocking the value of data:1. Data keeps growing at a fast pace and multi-format2. Data goes beyond SQL3. Data needs to reach everyone in the organisationJoin this webinar to learn how BigQuery, a serverless, cost-effective enterprise data warehouse, makes a difference in tackling those roadblocks – and realise a real competitive advantage through the pervasive use of data analytics and AI.Date: November 23, 2022 9:30 AM- 10:00 AM GMTClick on the link below to join this event.https://cloudonair.withgoogle.com/events/data-analytics-ai

malaminModerator

posted in AI and Machine Learning

Join us at Google Data Cloud Live: Vancouver

Google Data Cloud Live is coming to Vancouver and will feature technology leaders and data professionals who will share insights on how you can capitalize on the next wave of data solutions. You’ll have the opportunity to learn about the many ways that you and your organization can make smarter decisions and solve complex challenges with key innovations in AI, machine learning, and analytics. click on the link below to join this event.https://inthecloud.withgoogle.com/data-cloud-live-vancouver/register.html

malaminModerator

posted in AI and Machine Learning

Join at Google Data Cloud Live: Montréal

Google Data Cloud Live is coming to Montréal and will feature technology leaders and data professionals who will share insights on how you can capitalize on the next wave of data solutions. You’ll have the opportunity to learn about the many ways that you and your organization can make smarter decisions and solve complex challenges with key innovations in AI, machine learning, and analytics. Click on the link below to join this event:https://inthecloud.withgoogle.com/google-data-cloud-live-montreal-22/register.html

malaminModerator

posted in AI and Machine Learning

Accelerating ML development with optimized performance and cost

Successful machine learning deployments can depend on the ability of infrastructure to support the performance and budget requirements of a workload. Google’s open, flexible, and scalable AI infrastructure supports a wide variety of AI workloads, enabling customers to increase velocity to production, reduce costs, and to meet changing requirements over time. In this session, we discuss how to optimize across the AI stack with the latest GPUs and TPUs, fully-managed purpose-built AI infrastructure capabilities with Vertex AI, and state of the art solutions for demanding workloads. You'll also hear about how Uber, Cohere, Credit Karma, Arbor Biotechnologies and other enterprises are leveraging Google Cloud's AI Infrastructure to innovate, accelerate deployment, and drive business value.Speakers:Click on video below to watch it in detail: Extra Credit:Optimize training performance with Reduction Server on Vertex AI → https://goo.gle/3SE2VNX All sessions from Google Cloud Next → https://g

malaminModerator

posted in AI and Machine Learning

Google Cloud Next 22: top AI and ML sessions

Google Cloud Next starts this week, and features over a dozen sessions dedicated to helping organizations innovate with machine learning (ML) and inject artificial intelligence (AI) into their workflows. Whether you’re a data scientist looking for cutting-edge ML tools, a developer aiming to more easily build AI-powered apps, or a non-technical worker who wants to leverage AI for greater productivity, here are some you can’t miss AI and ML sessions that is summarise by Google Cloud content editor. Developing ML models faster and turning data into action For data scientists and ML experts, we’re offering a variety of sessions to help accelerate the training and deployment of models to production, as well to bridge the gap between data and AI. Top sessions include: ANA204: What's next for data analysts and data scientistsJoin this session to learn how Google Cloud can help your organization turn data into action, including overviews of the latest announcements and best practices for BigQ

malaminModerator

posted in AI and Machine Learning

How Twitter maximizes performance with BigQuery

How does a tweet go from one person to hundreds of millions of people? How does the data process so quickly? In this video of Architecting with Google Cloud, Priyanka chats with Gary and Saurabh from Twitter about how data from over 200 million users goes through the Twitter data center and Google Cloud. Watch along and learn how data stored across tens of thousands of BigQuery tables in Google Cloud runs millions of queries each month.Click on the video below to watch it in detail:Chapters:0:00 - Intro1:39 - How does Twitter process data?2:20 - How does Twitter’s data get to Google Cloud?3:34 - Twitter’s data migration architecture4:40 - Use cases for BigQuery at Twitter6:00 - How does Twitter manage storage?7:49 - How does Twitter organize data?10:31 - Data storage hierarchy & provisioning12:06 - How does Twitter secure & monitor data?13:24 - Twitter’s challenges for data at scale14:21 - BigQuery at Twitter15:10 - Wrap up Extra Credit:Twitter Google collab on BigQuery → http

malaminModerator

posted in AI and Machine Learning

Searching for extraterrestrials with Google Cloud

Can Google Cloud be used to search for extraterrestrial intelligence? In this episode of Serverless Expeditions, Developer Advocate Martin Omander chats with Raffy Traas, winner of the SETI Forward Award from SETI Institute about how he was able to search through radiofrequency data to find technosignatures. Watch to see how Google Cloud was used in the search for extraterrestrial intelligence!Click on the video below to watch it in detail:Chapters:0:00 - Intro0:39 - What are technosignatures?2:15 - Filtering out other signals3:29 - Telescope data analysis4:35 - How do you get the data from the telescope?6:05 - How did you process this data on Google Cloud?7:34 - What were the results?8:47 - What’s next for SETI & Raffy?10:25 - Wrap up

malaminModerator

posted in AI and Machine Learning

AudioLM: a Language Modeling Approach to Audio Generation

Learn about AudioLM, an audio generation framework that demonstrates long-term consistency (e.g., syntax in speech & melody in music) and high fidelity, with applications for speech synthesis and computer-assisted music. Click on the link the below to read it more detail.https://ai.googleblog.com/2022/10/audiolm-language-modeling-approach-to.html .

malaminModerator

posted in AI and Machine Learning

Unlock biology & medicine potential with AlphaFold on Google Cloud

The next answers to the mysteries of life and discovery of disease treatments have never felt more attainable with these no-cost solutions to run AlphaFold on Vertex AI. Stephanie Wong uncovers how AlphaFold has revolutionized the scientific community and walks through 3 ways to get access to it. Check out the AlphaFold public dataset to run custom queries on BigQuery, experiment on a smaller protein database using Vertex AI Workbench, and scale to hundreds of experiments using Vertex AI Pipelines.Click on the video below to watch it in detail: Chapters:0:00 - Intro0:34 - What is protein folding?1:19 - What is AlphaFold?2:58 - Considerations for running AlphaFold4:24 - AlphaFold Python notebook4:59 - AlphaFold batch inference solution on Vertex AI6:33 - Wrap up Extra Credit:AlphaFold BigQuery public dataset → https://goo.gle/3Em79pd AlphaFold notebook on Vertex AI Workbench → https://goo.gle/3ryXbcp AlphaFold batch inferencing solution on Vertex AI Pipelines → https://goo.gle/3V7OJhI

malaminModerator

posted in AI and Machine Learning

CCAI Platform goes GA: Faster time to value with AI for your Contact Center

Google Cloud CCAI Platform is launched and Generally Available! Learn how AI combined with an innovative and user focused CCaaS, can transform the Contact Center for EVERYONE: the end users, the CC business owners, and the agents!!Cloud built Contact Center AI (CCAI) to streamline and shorten this time to value, and CCAI Platform, Google Cloud newest addition, takes a crucial step in this effort by introducing end-to-end call center capabilities. Click on the link below to read it more detail.https://cloud.google.com/blog/products/ai-machine-learning/google-cloud-contact-center-ai-platform-now-ga

malaminModerator

posted in AI and Machine Learning

Google Cloud Delivers on the Promise of AI and Data Interoperability with New Medical Imaging Suite

Introducing Medical Imaging Suite: a new solution to help organizations transform imaging diagnostics by making imaging data accessible, interoperable, and useful.Learn more about the tools and products that are in this suite Click on the link below to read it more detail:https://www.googlecloudpresscorner.com/2022-10-04-Google-Cloud-Delivers-on-the-Promise-of-AI-and-Data-Interoperability-with-New-Medical-Imaging-Suite

manju@pluto7.comCommunity Member

posted in AI and Machine Learning

Supply Chain Intelligence Evolution with Connected Data

Customer’s need for a connected decisions(connected planning or bridging planning with execution) leads them to look for a Digital Twin, Control Tower or a Command Center. Most often business think there are standard software that addresses the need. In my two decade experience(since I started my career at Cisco). most softwares don’t even meet 70% of the need, hence customer end up building on their own. This leads to my point, that connecting data is essential for you to take the journey ahead and for which you need to start with a data foundation platform and then evolve. Traditionally, a supply chain control tower is defined as a connected, personalized dashboard of data, key business metrics, and events from across the supply chain. A control tower for supply chain allows businesses to better understand, prioritize, and resolve critical issues in real time. A smarter control tower should provide end-to-end visibility across the supply chain, especially in the event of unanticipate

malaminModerator

posted in AI and Machine Learning

How to Diagnose issues with Anthos Clusters on VMware

Learn how to troubleshoot issues with Anthos clusters running on VMWare using the gkectl command line tool. Additionally, learn how to generate snapshots you can send to Google Cloud support if further analysis is required.Click on video below to watch it in detail: Chapters0:00 Intro0:13 What is gkectl?0:53 How to diagnose Anthos admin cluster using gkectl ?1:36 How to fix Admin cluster issues?2:33 How to diagnose Anthos user cluster using gkectl?2:58 What is a snapshot?3:18 Snapshot creation process3:38 VMWare snapshot creation prerequisites4:00How to create a snapshot for admin cluster using gkectl Diagnosing cluster issues on VMWare → https://goo.gle/Diagnose_Anthos_On_Vm...

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