Little Red Riding Hood goes to visit her grandmother, carrying a basket of goods. Along the way, she stops to pick flowers and loses track of time. She meets a wolf who asks where she is going. Later, the wolf arrives at the grandmother's house first and eats her. He waits in her bed for Little Red Riding Hood. When she arrives, he tricks her into believing he is the grandmother until she notices his large teeth. She escapes and calls for help, and the woodsman rescues them by making the wolf spit out the grandmother.
Once upon a time in the middle of a thick forest stood a small cottage, the home of a pretty little girl known to everyone as Little Red Riding Hood. One day, her Mummy waved her goodbye at the garden gate, saying: "Grandma is ill. Take her this basket of cakes, but be very careful. Keep to the path through the wood and don't ever stop. That way, you will come to no harm." Little Red Riding Hood kissed her mother and ran off. "Don't worry," she said, "I'll run all the way to Grandma's without stopping."
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
2. Once upon a time, there was a little girl who lived in a village near the forest. Whenever, she went out, the little girl wore a red riding cloak, so everyone in the village called her Little Red Riding Hood. One morning, Little Red Riding Hood asked her mother if she could go to visit her grandmother as it had been awhile since they'd seen each other. "That's a good idea," her mother said. So they packed a nice basket for Little Red Riding Hood to take to her grandmother.
3. When the basket was ready, the little girl put on her red cloak and kissed her mother goodbye. "Remember, go straight to Grandma's house," her mother cautioned. "Don't dawdle along the way and please don't talk to strangers! The woods are dangerous. "Don't worry, mommy," said Little Red Riding Hood, "I'll be careful."
4. But when Little Red Riding Hood noticed some lovely flowers in the woods, she forgot her promise to her mother. She picked a few, watched the butterflies flit about for awhile, listened to the frogs croaking and then picked a few more. Little Red Riding Hood was enjoying the warm summer day so much, that she didn't notice a dark shadow approaching out of the forest behind her..
5. Suddenly, the wolf appeared beside her. "What are you doing out here, little girl?" the wolf asked in a voice as friendly as he could muster. "I'm on my way to see my Grandma who lives through the forest, near the brook," Little Red Riding Hood replied. Then she realized how late she was and quickly excused herself, rushing down the path to her Grandma's house. The wolf, in the meantime, took a shortcut..
6. The wolf, a little out of breath from running, arrived at Grandma's and knocked lightly at the door. "Oh thank goodness dear! Come in, come in! I was worried sick that something had happened to you in the forest," said Grandma thinking that the knock was her granddaughter. The wolf let himself in. Poor Granny did not have time to say another word, before the wolf gobbled her up!
7. The wolf let out a satisfied burp, and then poked through Granny's wardrobe to find a nightgown that he liked. He added a frilly sleeping cap, and for good measure, dabbed some of Granny's perfume behind his pointy ears. A few minutes later, Red Riding Hood knocked on the door. The wolf jumped into bed and pulled the covers over his nose. "Who is it?" he called in a crackly voice."It's me, Little Red Riding Hood.""Oh how lovely! Do come in, my dear," croaked the wolf.
8. When Little Red Riding Hood entered the little cottage, she could scarcely recognize her Grandmother. "Grandmother! You voice sounds so odd. Is something the matter?" she asked. "Oh, I just have touch of a cold," squeaked the wolf adding a cough at the end to prove the point. "But Grandmother! What big ears you have," said Little Red Riding Hood as she edged closer to the bed. "
9. The better to hear you with, my dear," replied the wolf."But Grandmother! What big eyes you have," said Little Red Riding Hood. "The better to see you with, my dear," replied the wolf. "But Grandmother! What big teeth you have," said Little Red Riding Hood her voice quivering slightly. "The better to eat you with, my dear," roared the wolf and he leapt out of the bed and began to chase the little girl.
10. Almost too late, Little Red Riding Hood realized that the person in the bed was not her Grandmother, but a hungry wolf. She ran across the room and through the door, shouting, "Help! Wolf!" as loudly as she could. A woodsman who was chopping logs nearby heard her cry and ran towards the cottage as fast as he could. He grabbed the wolf and made him spit out the poor Grandmother who was a bit frazzled by the whole experience, but still in one piece.
11. "Oh Grandma, I was so scared!" sobbed Little Red Riding Hood, "I'll never speak to strangers or dawdle in the forest again. "There, there, child. You've learned an important lesson. Thank goodness you shouted loud enough for this kind woodsman to hear you!” The woodsman knocked out the wolf and carried him deep into the forest where he wouldn't bother people any longer. Little Red Riding Hood and her Grandmother had a nice lunch and a long chat.