Artificial Intelligence is the most remarkable technology of our time, and it’s starting to affect every single aspect of our lives. Despite it’s massive impact, there is still so much misunderstanding about what it is, how it works, and what we can use it to do.
Ben Goertzel speaks about AI governance and control. He says “Whoever controls the AI, whoever owns the AI, controls and owns the world.” He goes on to say that it could be controlled by a few corporations or by the people via decentralization through blockchain. He also discusses that decentralized AI needs to be cheaper, smarter and more efficient than centralized systems.
Toufi Saliba speaks about how the promise of blockchain reduces the friction of business transactions and interactions while increasing security of AI with the intention of empowering indiividuals and the majority of the world, vs a few owners.
Chantel Costa speaks about the dichotomy of AI becoming centralized to a few entities vs being of available and accessible to the general public. Blockchain provides more transparency in AI by providing a transparent audit trail. She advocates that Google, Microsoft, Amazon, and Apple should not lead the way.
- Quantum Computers
- Artificial Intelligence
- VR Immersion
- Room Temp Superconductivity
- Nuclear Fusion
Barcelona-based Scaled Robotics built a Wall-E doppelgänger to navigate around and build maps of construction sites by fusing images, video, and data captured by its robots.
Machine Learning represents a new paradigm in programming, where instead of programming explicit rules in a language such as Java or C++, you build a system which is trained on data to infer the rules itself. But what does ML actually look like? In part one of Machine Learning Zero to Hero, AI Advocate Laurence Moroney walks through a basic “Hello World” example of building an ML model, introducing ideas which we’ll apply in later episodes to a more interesting problem: computer vision.
How data Governance can help your AI transformation? What is the purpose of data governance in Machine Learning and Artificial Intelligence? In this video, we will describe and give you examples why data governance is critical to the success of your business, organization, and government.
Dr Ben Goertzel is the Founder and CEO of SingularityNET and Chief Science Advisor for Hanson Robotics. In this discussion he posits a future based upon blockchain decentralized consensus networks and artificial intelligence.
Artificial intelligence (AI) has proven to be useful in many applications from automating cars to providing customer service responses. However, though many firms want to take advantage of AI to improve marketing, they lack a process by which to execute a Marketing AI project. This article discusses the use of AI to provide support for marketing decisions. Based on the established Cross-Industry Standard Process for Data Mining (CRISP-DM) framework, it creates a process for managers to use when executing a Marketing AI project and discusses issues that might arise. It explores how this framework was used to develop three cutting-edge Marketing AI applications.
This presentation teaches John Green Bot how to tell the difference between donuts and bagels using supervised learning.
Supervised learning is the process of learning with training labels, and is the most widely used kind of learning when it comes to AI. It helps with tagging photos on Facebook and filtering spam from your email. We’re going to start small today and show how just a single neuron (or perceptron) is constructed, and explain the differences between precision and recall. Next week, we’ll build our first neural network.
NVIDIA’s Bryan Catanzaro explains how recent breakthroughs in natural language understanding bring us one step closer to conversational AI.