NL3: Becoming an AI Engineer; Free Gen AI Training From Microsoft; AutoCoder - and more in this week's AI Roundup
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A Practical Guide to become an AI Engineer - Madhusudhan Konda
Are you a software engineer looking to transition into the exciting world of Artificial Intelligence? I am writing this guide that might be what you need!
This extensive guide serves as a blueprint to becoming an AI engineer. It has a step-by-step approach, giving you all the necessary knowledge and skills.
Here's some of what you'll learn:
Understand AI, Machine Learning and Generative AI in depth.
Look at real-life cases where industries are using AI to transform themselves.
Learn by doing with practical projects to apply what you’ve learned.
Work with the most popular tools and frameworks used in AI engineering, including Python libraries and APIs.
If you are making a career switch, upskilling your current role or if you’re simply curious about AI, my “Becoming an AI Engineer: Practical Guide for Software Engineers” is for you. Do check it out - I’ll be writing the chapters as quickly as I can!
Learn Azure Generative AI : Free Microsoft Azure Virtual Training Day!
Microsoft announced a free Generative AI Fundamentals course on 17th June 2-4.30pm BST - to discover and learn all about Generative AI fundamentals. This online live virtual event teaches you concepts of large language models and generative AI applications.
This is a free and open to the public event and you will be offered a coupon for 50% discount to sit on a Generative AI fundamentals Certification!
Register for the event here if you’d wish to!
Physicists using Generative AI-led to the discoveries.
A significant AI advancement is on its way in the world of physics.
The major challenge in physics is understanding the nature of materials’ behaviour. C
Understanding material’s behaviour is one of the major challenges in physics. In response, generative AI develops a potent new framework for automatically drawing phase diagrams. These illustrations show how applying external variables like pressure or temperature affects a material's characteristics - like density, malleability, strength or conductivity.
Scientists of the Massachusetts Institute of Technology and the University of Basel introduced a new generative AI to study phase diagrams of newly generated physical systems. The researchers stated that this machine learning is more efficient because, unlike the machine learning models that deal with the large data sets, generative AI uses small data to predict the outcomes.
This is not about AI replacing physicists. Instead, it's about creating a powerful partnership.
AutoCoder: The new Champion in code generation
The HumanEval benchmark test indicates that the current leader, AutoCoder, a newly released large language model (LLM), has overthrown GPT-4 Turbo as well as the recent GPT-4o model.
AutoCoder achieved a staggering 90.9% pass rate on the HumanEval test, surpassing GPT-4 Turbo's 90.2%. This says that Autocoder. The ability of AI models to produce human-quality code has significantly improved as a result.
One of AutoCoder's key strengths lies in its code interpreter. Unlike its predecessors like ChatGPT & ChatGpt-4o, AutoCoder can handle external packages, significantly expanding its applicability in real-world coding scenarios. This versatility empowers developers to tackle a broader range of coding challenges with the assistance of AutoCoder.
The capabilities introduced by AutoCoder are a defining advancement for AI code generation. It can be considered that future developments are possible through the enhancement of its performance and training methods. AI benefits for developers include better effectiveness, preciseness and fewer mistakes, and the ability to enter other coding horizons.
As AI-generated code becomes more prevalent, the need for robust validation and security checks becomes paramount. Researchers and developers must work together to ensure the safe and responsible integration of AI tools into the software development lifecycle.
Can’t deny - my favourite tool is for sure Canva!
Canva's recent "Canva Create" event was a treasure trove for designers and businesses alike. The Australian design giant unveiled a suite of exciting upgrades, including a powerful new subscription plan, an AI-infused design experience, and a revamped user interface.
Notable thing is - for larger organisations, Canva introduced Canva Enterprise. This subscription plan caters to businesses with increased storage needs and multiple user seats. It streamlines design workflows by centralizing design, content creation, and collaboration tools. Additionally, enterprise-grade security features like multi-factor authentication and data encryption ensure your creative assets are protected.
Also, Canva's AI playground, Magic Studio, received a significant upgrade. It can now generate stunning visuals from your written descriptions! With "Magic Media" and "Magic Design," you can create graphics, icons, and high-quality presentations based on simple text prompts.
Canva's core interface received a complete makeover, focusing on improved editing and collaboration. The streamlined interface boasts a contextual toolbar that provides you with the right tools at the right time, including easy access to background removal and Magic Studio's AI features. The customisable homepage allows for quick access to your favourite designs, folders, and templates, while the advanced search makes finding content a breeze.
Canva understands that different teams have different design needs - to address this, they've introduced "Canva Work Kits." These are customisable template collections specifically designed for various business units such as HR, sales, marketing etc!
With powerful AI features, a focus on streamlined workflows, and an enterprise-grade subscription plan, Canva caters to both individual creators and large organisations.
ThousandEyes Predicts and Fixes Outages
Enter the new era of internet performance and know how artificial intelligence is paving its way. ThousandEyes from Cisco introduced Digital Experience Assurance or DXA – a series of AI-based advanced network tools that shift from responding to threats to predicting them.
DXA is not just another tool to be used for monitoring a patient. It employs advanced AI to scan the network data in real-time on a substantial basis. This way, it not only diagnose existing issues but also proactively anticipate problems that are likely to happen in the future.
The company has hinted at the development of even more advanced AI features - where AI not only predicts and fixes outages but also personalises network performance optimisation based on specific user needs and business requirements.
ThousandEyes' DXA marks a paradigm shift in network management - it empowers businesses to achieve unprecedented levels of network reliability and user experience by harnessing the power of AI.
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