#060 - Transformer Models: The Next Big Thing in AI, Sanctuary AI is Building the Future of Work with Humanoid General-Purpose Robots, How Microsoft is Leading the New Era of AI.
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AI BYTE # 1 📢 : How Sanctuary AI is Building the Future of Work with Humanoid General-Purpose Robots
⭐ The world is facing a labor crisis. As birth rates decline and populations age, there are not enough workers to fill the growing demand for various tasks and services.
According to the World Economic Forum, by 2025, there will be a global shortfall of 85 million workers, costing the global economy $8.5 trillion.
To address this challenge, we need a technology-based solution that can augment human capabilities and perform work across different domains and environments. That’s where Sanctuary AI comes in.
Sanctuary AI is a Vancouver-based company that has raised over $100 million Canadian dollars to pursue its vision of labor as a service. It makes a 5-foot, 7-inch general-purpose humanoid robot called Phoenix, powered by an AI system called Carbon.
Phoenix is not your typical robot. It has human-like intelligence and a humanoid physical form that can do anything a person can do. It can walk, talk, press buttons, pull levers, operate machines, collect trash, do security, and more.
It can learn new skills and tasks through natural language instructions and demonstrations. It can reason, plan, and execute actions in complex and dynamic situations.
Phoenix is also not your typical invention. It has been recognized by TIME as one of the Best Inventions of 2023, in the highly competitive Robotics category.
It is the only humanoid general-purpose robot on the list, and the only Canadian company in its category. It has also been featured on Forbes, Wired, GeekWire, and other media outlets.
Phoenix is already making an impact in the real world. Sanctuary AI has successfully deployed Phoenix at commercial sites in partnership with Canadian Tire Corporation, one of Canada’s largest retailers. Phoenix has demonstrated its ability to perform various tasks in warehouses, such as picking, packing, sorting, scanning, and labeling products.
Phoenix is not just a robot. It is a solution to the labor crisis. It is a partner to human workers. It is a catalyst for innovation and productivity. It is a glimpse into the future of work.
If you are interested in learning more about Sanctuary AI and Phoenix, you can visit their website at sanctuary.ai.
AI BYTE # 2 📢 : How Microsoft is Leading the New Era of AI
⭐ In this post, I want to share some insights from Microsoft’s annual letter, published today in their Annual Report 2023, where they outline their vision and progress in the AI revolution.
Microsoft’s mission is to empower every person and every organization on the planet to achieve more. To do this, they are leading the next generation of AI, which combines natural language and powerful reasoning to help us interact with data and create value faster than ever. They call this Copilot, an everyday AI companion that works across their products and experiences.
Microsoft is also democratizing AI, making it accessible and affordable for everyone. They are investing in cloud infrastructure, data platforms, foundation models, developer tools, low-code/no-code solutions, business applications, security solutions, and more. They are also providing AI training and certification for millions of people around the world.
Microsoft is not only using AI to grow their business, but also to create positive impact for society and the environment. They are committed to responsible AI, protecting privacy, advancing human rights, bridging the digital divide, addressing climate change, and supporting humanitarian action.
Microsoft’s results speak for themselves. In fiscal year 2023, they delivered a record $211 billion in revenue and over $88 billion in operating income. They also surpassed $20 billion in annual revenue for their security business, $15 billion for LinkedIn, $5 billion for Dynamics, and $1 billion for Windows 365.
Microsoft’s letter shows how they are embracing the AI era with conviction and responsibility. They are not only creating value for their shareholders, but also for their customers, partners, employees, and communities. They are setting an example for how technology can be a force for good in the world.
If you want to learn more about Microsoft’s vision and progress in AI, you can read their full letter here. You can also check out some of the latest trends and innovations in AI here.
AI BYTE # 3 📢 - Transformer Models: The Next Big Thing in AI
⭐ Y you have probably heard of transformer models, but do you know what does it really mean?
These are neural networks that learn context and meaning by tracking relationships in sequential data, such as text, images, or video.
In this post, I will explain what transformer models are, why they are so powerful, and how they are transforming various domains and applications.
Transformer models were first introduced by Google researchers in 2017 as a new way of doing machine translation.
Unlike previous methods that used recurrent or convolutional neural networks, transformer models rely on a technique called attention or self-attention. This technique allows the model to focus on the most relevant parts of the input and output sequences, and capture both short-term and long-term dependencies among the data elements.
Since then, transformer models have been extended and improved by many researchers and companies, setting new records in natural language processing, computer vision, speech recognition, and other tasks.
Some of the most famous examples of transformer models are BERT, GPT-3, Megatron-Turing NLG, and AlphaFold2.
One of the main advantages of transformer models is that they can learn from large amounts of unlabeled data using self-supervised learning. This means that they can discover patterns and structures in the data without human intervention or guidance.
This enables them to leverage the vast amount of information available on the web and in corporate databases, and generate accurate and diverse predictions.
Another advantage of transformer models is that they can scale well with parallel computing. This means that they can process multiple data elements at the same time using multiple processors or GPUs. This allows them to handle longer and more complex sequences, and train faster and more efficiently.
Transformer models are already having a huge impact on various domains and applications. For example:
They are enabling real-time translation and transcription of speech and text, making communication and collaboration more accessible and inclusive.
They are helping researchers understand the structure and function of proteins, which are the building blocks of life, and accelerate drug discovery and development.
They are detecting trends and anomalies in data to prevent fraud, optimize manufacturing, personalize recommendations, and improve healthcare.
They are generating realistic and creative content such as text, images, music, and code, opening new possibilities for entertainment and education.
Transformer models are not without challenges or limitations. For instance:
They require a lot of computing power and memory to train and run, which can be costly and environmentally unfriendly.
They can inherit or amplify bias or toxicity from the data they learn from, which can have negative social and ethical consequences.
They can be hard to interpret or explain, which can reduce trust and accountability.
These challenges require careful research and development to ensure that transformer models are used responsibly and beneficially.
There are many ongoing efforts to address these issues, such as creating simpler or sparser models, reducing carbon footprint, detecting and mitigating bias or toxicity, and enhancing transparency and explainability.
Transformer models are one of the most exciting and promising innovations in AI. They have shown remarkable capabilities in learning from data and generating predictions across various domains and applications.
They have also opened new avenues for research and development in AI. It is the next big thing in AI.
