AI and Machine Learning
Introduce efficiencies to improve operations and add intelligence for digital transformation of products or services.
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I absolutely loved my conversation with Cai GoGwilt from Ironclad last week for our C2C Navigators offering.GoGwilt is a cellist, a programmer, and oh yes, CTO of Ironclad, the legal technology firm he co-founded. We discussed how AI is used to improve the contracting collaboration process and so, so much more.Check out the key conversation clips in the link below. What is sticking with you? Have you used AI? Did you know AI could be using in legal contracting? Tell me below
Why is the big data and ML space growing so rapidly versus other cloud services? Would love to get everyone’s perspective. From my perspective, I think companies are realizing the true power of cloud lies in quickly leveraging big data and ML technologies (versus just staying on IaaS or other PaaS) since they can enable several use cases (depending on the industry) and they do not have to manage the infrastructure. The key seems to be in the speed in time to value. Thoughts? What use case are you leveraging for your industry?
What I see.. What YOU see... But only if you registered for today’s Navigator talk with Cai GoGwilt. They just rounded out Series D funding for 100M and are pioneering legal tech. What questions would you ask Cai if you were able to meet him? See you soon!
Share your thoughts on the latest news: Automation Anywhere and Google Cloud Partner to Enable Enterprises to Automate Common Business Processes
Big news yesterday, shared in this press release and covered by a lot of tech publications. Automation Anywhere, a leader in robotic process automation (RPA), and Google Cloud today announced a strategic, multi-year collaboration to accelerate intelligent automation adoption with enterprises on a global scale.With this partnership, Automation Anywhere’s Automation 360 platform will be available on Google Cloud, and the two companies will mutually develop AI- and RPA-powered solutions, bring RPA capabilities to multiple Google Cloud products, and closely align go-to-market teams to help global businesses scale RPA capabilities. Share your thoughts! How does this news impact your adoption of RPA, AI, or ML? Anyone already leveraging Automation Anywhere’s platform? Are you one of the companies investing in automation as the quote below indicates? If so, what’s driving that adoption? According to new research from Automation Anywhere, more than half of businesses plan to increase their inv
The Healthcare Consent Management API is generally available.Jameson Rogers’s article is talking about it. Do you think that will help us? Both as programmers - researchers and as human beings?https://cloud.google.com/blog/topics/healthcare-life-sciences/google-cloud-healthcare-consent-management-api-generally-available
Gartner has named Google a Leader in its 2021 Magic Quadrant for Cloud AI Developer Services. We believe this recognition is based on Gartner’s evaluation of Google Cloud’s language, vision, conversational, and structured data services and solutions for developers. Gartner’s recognition is also a reflection of the confidence and satisfaction that customers have in our products.Read more and get a copy of the report here. Useful? Rate this article thumbs up !
FIH Mobile used Google’s Cloud AutoML Vision and reduced their defect escape rate to 10%, while the time to inspect each component decreased dramatically to 0.3 seconds, or 1.3 seconds once fixture movement time is taken into account.This is really amazing! And you can read the article here.Has anyone in our community used AutoML Vision? Can you share with us the idea of the project, the issues (if any), and how you overcame them?
This is a great blog post from one of google’s AI/ML Developer Advocacy Managers, Karl Weinmesiter, one how to invoke BigQueryML models directly into your Google Sheets! The post covers the: Problem statement and use case How to build and train ML models (ARIMA in this post) directly within Sheets Code snippets for how the models work Summary to bring it all together and output the resultsCheck it out here
A self-study guide for aspiring machine learning practitionersMachine Learning Crash Course features a series of lessons with video lectures, real-world case studies, and hands-on practice exercises.30+ exercises 25 lessons 15 hours Lectures from Google researches Real-world case studies Interactive visualizations of algorithms in actionAccess it here
C2C General Manager shared this lengthy blogpost by Jeff Dean, Senior Fellow and SVP of Google Research and Health, on behalf of the entire Google Research community. Jeff said, “This is a very lengthy and complex read but is rich with detail, insights, and ideas.”This is a long post, but is grouped into many different sections, which you can jump to directly using the table below. Hopefully, there’s something interesting in here for everyone! · COVID-19 and Health · AutoML · ML for Medical Diagnostics · Understanding ML Algorithms and Models · Weather, Environment and Climate Change · Algorithmic Foundations and Theory · Accessibility · Machine Perception · Applications of ML to Other Fields · Robotics · Responsible AI · Quantum Computing · Natural Language Understanding · Supporting Developers and Researchers · Language Translation · Open Datasets and Dataset Search · Machine Learning Algorithm
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