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How does a one-millimetre worm help win four Nobel Prizes? In this episode, we explore how C. elegans became one of the most influential organisms in modern biology — not because of its size, but because of its community.

Researchers, beginning with Sydney Brenner’s vision, built an ecosystem of radical openness: shared strains, shared annotations, shared tools, shared knowledge. This culture powered breakthroughs in apoptosis, GFP, RNA interference, and microRNAs, each recognised with a Nobel Prize.

We discuss how the CGC, WormBase, WormAtlas, open imaging libraries, and collaborative genetics transformed a tiny worm into a global scientific powerhouse. It’s the story of a field that chose to share — and in doing so, changed biology.

Key themes: • The collaborative backbone behind worm research • Why sharing strains and data accelerated Nobel-winning discoveries • How open tools shaped genetics, neuroscience, and ageing research • The social and scientific architecture of a uniquely supportive community • Why C. elegans is still leading modern multi-omics and connectomics

Based on the research article:🎧 Subscribe to the WOrM Podcast “From nematode to Nobel: How community-shared resources fueled the rise of Caenorhabditis elegans as a research organism” Victor R. Ambros, Martin Chalfie, Aric L. Daul, Andrew Z. Fire, David H. Hall, H. Robert Horvitz, Craig C. Mello, Gary Ruvkun, Nathan E. Schroeder, Paul W. Sternberg & Ann E. Rougvie. PNAS (2025) 🔗 https://doi.org/10.1073/pnas.2522808122

🎧 Subscribe to the WOrM Podcast Whole-organism stories from molecules to behaviour.

This podcast is generated with artificial intelligence and curated by Veeren. If you’d like your publication featured on the show, please get in touch.

📩 More info: 🔗 ⁠⁠www.veerenchauhan.com⁠⁠ 📧 [email protected]

The relationship between data governance and AI quality is more critical than ever. As organizations rush to implement AI solutions, many are discovering that without proper data hygiene and testing protocols, they're building on shaky foundations. How do you ensure your AI systems are making decisions based on accurate, appropriate information? What benchmarking strategies can help you measure real improvement rather than just increased output? With AI now touching everything from code generation to legal documents, the consequences of poor quality control extend far beyond simple errors—they can damage reputation, violate regulations, or even put licenses at risk. David Colwell is the Vice President of Artificial Intelligence and Machine Learning at Tricentis, a global leader in continuous testing and quality engineering. He founded the company’s AI division in 2018 with a mission to make quality assurance more effective and engaging through applied AI innovation. With over 15 years of experience in AI, software testing, and automation, David has played a key role in shaping Tricentis’ intelligent testing strategy. His team developed Vision AI, a patented computer vision–based automation capability within Tosca, and continues to pioneer work in large language model agents and AI-driven quality engineering. Before joining Tricentis, David led testing and innovation initiatives at DX Solutions and OnePath, building automation frameworks and leading teams to deliver scalable, AI-enabled testing solutions. Based in Sydney, he remains focused on advancing practical, trustworthy applications of AI in enterprise software development. In the episode, Richie and David explore AI disasters in legal settings, the balance between AI productivity and quality, the evolving role of data scientists, and the importance of benchmarks and data governance in AI development, and much more. Links Mentioned in the Show: Tricentis 2025 Quality Transformation ReportConnect with DavidCourse: Artificial Intelligence (AI) LeadershipRelated Episode: Building & Managing Human+Agent Hybrid Teams with Karen Ng, Head of Product at HubSpotRewatch RADAR AI  New to DataCamp? Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

Join Caron and Maya for an exclusive briefing on accessing our engaged global communities.

We'll reveal: • Premium sponsorship opportunities across three distinct segments: AI/Tech (100K+), Business (84K+), and Lifestyle (160K+) • Exclusive AIBizEx sponsorship opportunities for AI-powered business tools • Strategic local event sponsorship opportunities in major global markets

When: Sept 9, 8:30 AM EDT/1:30 PM BST Limited spots available. Registration required.

Perfect for: Tech companies, B2B service providers, and brands seeking expanded local, national and/or international exposure.

We can customize packages based on your needs: book a call!

Key metrics: • 48% email open rates • Self-identified affinity groups • Proven track record of 300+ RSVPs for virtual events • Successful events across multiple time zones.

We host communities across USA, UK, Canada, Europe, South America, India and Australia.

• USA:

• New York: 125,000+
• San Francisco/Silicon Valley: 10,000+
• Los Angeles: 13,000+

• UK:

• London: 54,000+

• Canada:

• Toronto: 44,000+

• India:

• Delhi: 16,000+
• Mumbai: 16,000+

• Australia:

• Sydney: 8,250+
• Melbourne: 2,500+

• South America:

• São Paulo: 12,500+
• Santiago: 2,700+

Limited spots available. Registration required.

Join Caron and Maya for an exclusive briefing on accessing our engaged global communities.

We'll reveal: • Premium sponsorship opportunities across three distinct segments: AI/Tech (100K+), Business (84K+), and Lifestyle (160K+) • Exclusive AIBizEx sponsorship opportunities for AI-powered business tools • Strategic local event sponsorship opportunities in major global markets

When: Sept 9, 8:30 AM EDT/1:30 PM BST Limited spots available. Registration required.

Perfect for: Tech companies, B2B service providers, and brands seeking expanded local, national and/or international exposure.

We can customize packages based on your needs: book a call!

Key metrics: • 48% email open rates • Self-identified affinity groups • Proven track record of 300+ RSVPs for virtual events • Successful events across multiple time zones.

We host communities across USA, UK, Canada, Europe, South America, India and Australia.

• USA:

• New York: 125,000+
• San Francisco/Silicon Valley: 10,000+
• Los Angeles: 13,000+

• UK:

• London: 54,000+

• Canada:

• Toronto: 44,000+

• India:

• Delhi: 16,000+
• Mumbai: 16,000+

• Australia:

• Sydney: 8,250+
• Melbourne: 2,500+

• South America:

• São Paulo: 12,500+
• Santiago: 2,700+

Limited spots available. Registration required.

Join Caron and Maya for an exclusive briefing on accessing our engaged global communities.

We'll reveal: • Premium sponsorship opportunities across three distinct segments: AI/Tech (100K+), Business (84K+), and Lifestyle (160K+) • Exclusive AIBizEx sponsorship opportunities for AI-powered business tools • Strategic local event sponsorship opportunities in major global markets

When: Sept 9, 8:30 AM EDT/1:30 PM BST Limited spots available. Registration required.

Perfect for: Tech companies, B2B service providers, and brands seeking expanded local, national and/or international exposure.

We can customize packages based on your needs: book a call!

Key metrics: • 48% email open rates • Self-identified affinity groups • Proven track record of 300+ RSVPs for virtual events • Successful events across multiple time zones.

We host communities across USA, UK, Canada, Europe, South America, India and Australia.

• USA:

• New York: 125,000+
• San Francisco/Silicon Valley: 10,000+
• Los Angeles: 13,000+

• UK:

• London: 54,000+

• Canada:

• Toronto: 44,000+

• India:

• Delhi: 16,000+
• Mumbai: 16,000+

• Australia:

• Sydney: 8,250+
• Melbourne: 2,500+

• South America:

• São Paulo: 12,500+
• Santiago: 2,700+

Limited spots available. Registration required.

For the first time since they've been a party of five, all of the Analytics Power Hour co-hosts assembled in the same location. That location? The Windy City. The occasion? Chicago's first ever MeasureCamp! The crew was busy throughout the day inviting attendees to "hop on the mic" with them to answer various questions. We covered everything from favorite interview questions to tips and tricks, with some #hottake questions thrown in for fun. During the happy hour at the end of the day, we also recorded a brief live show, which highlighted some of the hosts' favorite moments from the day. Listen carefully and you'll catch an audio cameo from Tim's wife, Julie! And keep an eye on the MeasureCamp website to find the coolest way to spend a nerdy Saturday near you (Bratislava, Sydney, Dubai, Stockholm, Brussels, and Istanbul are all coming up before the end of the year!). For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Join Kirk, Sydney, and Jenny as they discuss self-care through the 30-30-4-30 walking challenge, emphasizing its transformative benefits. They highlight setting boundaries, resilience, and the importance of community support. The conversation extends to military to civilian life transitions, healthy workplace cultures, and mentorship in the data center industry.

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• 02Learn how to set-up continuous change monitoring and alerting for your AD environment.
• 03Learn how to improve employee productivity and reduce help desk costs with password self-service, SSO, and password sync.
• 04Know the best practices for Active Directory management from across the globe.
• 05Know how to combat sophisticated attacks with advanced log management & security auditing techniques.
• 06Consult with our experts. Discuss your Active Directory and IT security challenges with them.

Government Blockchain Association’s Monthly Public Free Blockchain and Finance Webinar...current state of Digital Assets Government Blockchain Association’s Monthly Public Free Blockchain and Finance Webinar Wednesday, 17th April at 10am EDT, listen as Paul Dowding has a discussion with Chris Smithmeyer about the current state of digital assets for both Crypto/DeFi & TradFi. Join this free public GBA Webinar at https://meet.google.com/joe-rjwn-ibu Dr. Smithmyer is the CEO/co-founder of Black Wallet Limited. He is the author of over a dozen cryptocurrency and blockchain books including several #1 best sellers. He is a speaker at major national and international events and a MBA Professor (a) at Doane University and a Law Professor (a) at Regent University. Paul Dowding has worked over 34 years in financial operations management, innovation, design and re-engineering. He has designed a patented DLT accounting solution – TapestryX. (https://L4SCorp.com) He has previously held management positions at major global banks, brokers and fund managers and consulted independently. He has worked and lived in London, New York, Singapore and Sydney and traveled extensively throughout the world. Paul holds a B.Sc. Hons (So’ton) Aeronautics and Astronautics. He is an Associate Member of The Institute of Mechanical Engineers, and has previously held NASD Series 7, 63 and 24 licenses. GBA's Blockchain and Financial Enterprises Webinar at https://meet.google.com/joe-rjwn-ibu GBA is a global non-profit business community with public sector members in over 500 government offices worldwide, private sector professionals joined in over 50 working groups to use blockchain & related technologies to solve public sector challenges. GBA's next in person event is the Future of Money Governance and Law, May 2-3 at 1777 F St NW, Washington DC. For more information go to gbaglobal.org/FOMGL GBA's Blockchain and Financial Enterprises Webinar at https://meet.google.com/joe-rjwn-ibu For further information contact Bob Miko, [email protected] 203 378 2803 Bob Miko Event Producer Pacific Dialogue pacificdialogue.com 203 378 2803

For our February meetup we're exciting to announce that we now have a double session.

First off Barry Smart will be presenting Microsoft Fabric & Your Data Strategy: A Decision Makers Guide

Barry has worked in the technology industry for almost 30 years. During the early stage of his career he worked in Australia for 3 years delivering a new system to automate Sydney's water treatment and distribution network. He then returned to Scotland where he spent his formative years as chief architect for ScottishPower's energy trading business. He then moved into a leadership role with Hymans Robertson, the UK's largest independent firm of consulting actuaries, where he spearheaded their adoption of cloud technology. In 2019 he took a career break to complete a Masters in Artificial Intelligence. He now works as Director for Data and AI at endjin, where he helps organisations around the world to deliver impact through data. He specialises in harnessing cloud technology and the latest developments in analytics, machine learning and AI. In his spare time, Barry enjoys mountain biking and playing the trombone in a big band.

Our 2nd session for the evening: Microsoft Power BI Usage Analysis: a practical approach to measuring and improving BI performance

Achieving success with Power BI within an organization goes beyond the initial implementation and maintenance. To unlock its full strategic potential, we must ensure it's not only properly implemented but also widely adopted and effectively used.

In thier presentation, Anna and Gennadii will discuss how Power BI usage data can be analysed to provide a solid ground for optimising the Power BI environment and facilitate a wide range of data and analytics initiatives.

They will share a few client stories, the fundamental questions that usage analysis should answer, the key metrics and KPIs that should be tracked, and actionable strategies to transform Power BI experience.

To demonstrate their approach, they will introduce Accton Auditor, a comprehensive BI usage analysis solution tightly integrated with Power BI.

OPEN DATA CHALLENGE: This is your opportunity to showcase your talent using Microsoft Fabric using Open Data. This month the theme for the challenge is Aviation data, rolling over from last month:

https://atmdata.github.io/sources/

You'll have the opportunity to present a short (max 5 minute) presentation to show road report and and other aspects of Microsoft Fabric used in creating your solution. Please bring a laptop to present, or contact us in advance.

AGENDA: 1830 - 18:45 : Introduction, networking, pizza & drinks 18:45 - 19:00 : Open Data Challenge 19:00 - 20:00 : Microsoft Fabric & Your Data Strategy: A Decision Makers Guide 20:00 - 20:45 : Microsoft Power BI Usage Analysis: a practical approach to measuring and improving BI performance

VENUE: We will meet at the Nigel Frank Offices at 60 Great Tower Street. If you've not been there before, it's just a little further up the street from Brewdog. Google Maps link to help you find the building: https://goo.gl/maps/GRZWr5LfScZhApu6A

Discover how Azure Load Testing integrates with Azure Kubernetes Service (AKS) for performance optimization.

In this session, we will showcase an automated load testing solution for AKS, that serves as a release gate for a minimal Service Level Objective (SLO). Learn how to utilize Azure Load Testing to identify the right-size Pod configuration for your AKS deployment using a GitHub Actions workflow and test configuration matrix.

This is the fifth in a 7-part online series hosted by the Microsoft Reactor.

Learn more here-https://aka.ms/aks-load-testing

Speaker BIO- Anthony Shaw Anthony is from Sydney, Australia and is a contributor to many open-source communities. Running and contributing to several popular open-source tools for DevOps, Security, Automation and Code Quality. He has been recognized for his contribution to open source, including as Fellow of the Python Software Foundation and member of the Apache Software Foundation. Anthony runs a Python blog and YouTube channel and has recently published a book on the Python compiler.

Social Handle of the speaker LinkedIn-https://www.linkedin.com/in/anthonypshaw/ Twitter- @anthonypjshaw

Zoom Link

https://voxel51.com/computer-vision-events/august-24-meetup-apac/

Removing Backgrounds Automatically or with a User's Language

Image matting, also known as removing background, refers to extracting the accurate foregrounds in the image, which benefits many downstream applications such as film production and augmented reality. To solve this ill-posed problem, previous methods require extra user inputs with large amounts of manual effort such as trimap or scribbles. In this session, we will introduce our research works, which allow users to automatically remove the background or even flexibly choose the specific foreground by user's language. We'll also show some fancy demos and illustrate some downstream applications.

Jizhizi Li has just finished her Ph.D. study in Artificial Intelligence at the University of Sydney. With several papers published in top-tier conferences and journals including CVPR, IJCV, IJCAI and Multimedia, her research interests include computer vision, image matting, multi-modal learning, and AIGC.

Self-Supervised Representative Learning for Action Recognition in Videos

Video data is exploding and drawing intelligence from it is increasing in importance. Self-supervised learning has grown in popularity because it enables the use of large data sets without having large labeled data. Action recognition in videos has always been a challenging task that is well-suited to leverage self supervised learning. This talk will cover representative learning pretext task with approaches such as contrastive learning and masked auto-encoders for videos.

Vidhya Vinay is a co-founder of Streamingo.ai, an AI startup that works on human activity detection in videos. As part of her work at Streamingo, Vidhya has worked on deep learning for speech recognition, NLP and computer vision.

AI at the Edge: Optimizing Deep Learning Models for Real-World Applications

As AI technology continues to advance, there is a growing demand for deep learning models to tackle more complex tasks, particularly on edge devices. However, real-time performance and hardware constraints can present significant challenges in deploying these models on such devices. At SightX, we have been exploring ways to optimize deep learning models for top performance on edge devices while minimizing degradation. In this lecture, we will share our insights and techniques for deploying AI on edge devices, specifically focusing on hardware-aware optimization of deep learning models. We’ll review practical ways to effectively deploy deep learning models in real-time scenarios.

Raz Petel, SightX’s Head of AI, has been tackling Computer Vision challenges with Deep Learning since 2015, aiming to enhance their efficiency, speed, compactness, and resilience

Zoom Link

https://voxel51.com/computer-vision-events/august-24-meetup-apac/

Removing Backgrounds Automatically or with the User's Native Language

Image matting, also known as removing background, refers to extracting the accurate foregrounds in the image, which benefits many downstream applications such as film production and augmented reality. To solve this ill-posed problem, previous methods require extra user inputs with large amounts of manual effort such as trimap or scribbles. In this session, we will introduce our research, which allows user to automatically remove the background or even flexibly choose the specific foreground by a user's native language. We'll also show some fancy demos and illustrate some downstream applications.

Jizhizi Li has just finished her Ph.D. study in Artificial Intelligence at the University of Sydney. With several papers published in top-tier conferences and journals including CVPR, IJCV, IJCAI and Multimedia, her research interests include computer vision, image matting, multi-modal learning, and AIGC.

Self-Supervised Representative Learning for Action Recognition in Videos

Video data is exploding and drawing intelligence from it is increasing in importance. Self-supervised learning has grown in popularity because it enables the use of large data sets without having large labeled data. Action recognition in videos has always been a challenging task that is well-suited to leverage self supervised learning. This talk will cover representative learning pretext task with approaches such as contrastive learning and masked auto-encoders for videos.

Vidhya Vinay is a co-founder of Streamingo.ai, an AI startup that works on human activity detection in videos. As part of her work at Streamingo, Vidhya has worked on deep learning for speech recognition, NLP and computer vision.

AI at the Edge: Optimizing Deep Learning Models for Real-World Applications

As AI technology continues to advance, there is a growing demand for deep learning models to tackle more complex tasks, particularly on edge devices. However, real-time performance and hardware constraints can present significant challenges in deploying these models on such devices. At SightX, we have been exploring ways to optimize deep learning models for top performance on edge devices while minimizing degradation. In this lecture, we will share our insights and techniques for deploying AI on edge devices, specifically focusing on hardware-aware optimization of deep learning models. We’ll review practical ways to effectively deploy deep learning models in real-time scenarios.

Raz Petel, SightX’s Head of AI, has been tackling Computer Vision challenges with Deep Learning since 2015, aiming to enhance their efficiency, speed, compactness, and resilience

Zoom Link

https://voxel51.com/computer-vision-events/august-24-meetup-apac/

Removing Backgrounds Automatically or with a User's Language

Image matting, also known as removing background, refers to extracting the accurate foregrounds in the image, which benefits many downstream applications such as film production and augmented reality. To solve this ill-posed problem, previous methods require extra user inputs with large amounts of manual effort such as trimap or scribbles. In this session, we will introduce our research works, which allow users to automatically remove the background or even flexibly choose the specific foreground by user's language. We'll also show some fancy demos and illustrate some downstream applications.

Jizhizi Li has just finished her Ph.D. study in Artificial Intelligence at the University of Sydney. With several papers published in top-tier conferences and journals including CVPR, IJCV, IJCAI and Multimedia, her research interests include computer vision, image matting, multi-modal learning, and AIGC.

Self-Supervised Representative Learning for Action Recognition in Videos

Video data is exploding and drawing intelligence from it is increasing in importance. Self-supervised learning has grown in popularity because it enables the use of large data sets without having large labeled data. Action recognition in videos has always been a challenging task that is well-suited to leverage self supervised learning. This talk will cover representative learning pretext task with approaches such as contrastive learning and masked auto-encoders for videos.

Vidhya Vinay is a co-founder of Streamingo.ai, an AI startup that works on human activity detection in videos. As part of her work at Streamingo, Vidhya has worked on deep learning for speech recognition, NLP and computer vision.

AI at the Edge: Optimizing Deep Learning Models for Real-World Applications

As AI technology continues to advance, there is a growing demand for deep learning models to tackle more complex tasks, particularly on edge devices. However, real-time performance and hardware constraints can present significant challenges in deploying these models on such devices. At SightX, we have been exploring ways to optimize deep learning models for top performance on edge devices while minimizing degradation. In this lecture, we will share our insights and techniques for deploying AI on edge devices, specifically focusing on hardware-aware optimization of deep learning models. We’ll review practical ways to effectively deploy deep learning models in real-time scenarios.

Raz Petel, SightX’s Head of AI, has been tackling Computer Vision challenges with Deep Learning since 2015, aiming to enhance their efficiency, speed, compactness, and resilience

Zoom Link

https://voxel51.com/computer-vision-events/august-24-meetup-apac/

Removing Backgrounds Automatically or with the User's Native Language

Image matting, also known as removing background, refers to extracting the accurate foregrounds in the image, which benefits many downstream applications such as film production and augmented reality. To solve this ill-posed problem, previous methods require extra user inputs with large amounts of manual effort such as trimap or scribbles. In this session, we will introduce our research, which allows user to automatically remove the background or even flexibly choose the specific foreground by a user's native language. We'll also show some fancy demos and illustrate some downstream applications.

Jizhizi Li has just finished her Ph.D. study in Artificial Intelligence at the University of Sydney. With several papers published in top-tier conferences and journals including CVPR, IJCV, IJCAI and Multimedia, her research interests include computer vision, image matting, multi-modal learning, and AIGC.

Self-Supervised Representative Learning for Action Recognition in Videos

Video data is exploding and drawing intelligence from it is increasing in importance. Self-supervised learning has grown in popularity because it enables the use of large data sets without having large labeled data. Action recognition in videos has always been a challenging task that is well-suited to leverage self supervised learning. This talk will cover representative learning pretext task with approaches such as contrastive learning and masked auto-encoders for videos.

Vidhya Vinay is a co-founder of Streamingo.ai, an AI startup that works on human activity detection in videos. As part of her work at Streamingo, Vidhya has worked on deep learning for speech recognition, NLP and computer vision.

AI at the Edge: Optimizing Deep Learning Models for Real-World Applications

As AI technology continues to advance, there is a growing demand for deep learning models to tackle more complex tasks, particularly on edge devices. However, real-time performance and hardware constraints can present significant challenges in deploying these models on such devices. At SightX, we have been exploring ways to optimize deep learning models for top performance on edge devices while minimizing degradation. In this lecture, we will share our insights and techniques for deploying AI on edge devices, specifically focusing on hardware-aware optimization of deep learning models. We’ll review practical ways to effectively deploy deep learning models in real-time scenarios.

Raz Petel, SightX’s Head of AI, has been tackling Computer Vision challenges with Deep Learning since 2015, aiming to enhance their efficiency, speed, compactness, and resilience