Cortex is built on a new public chain called Cortex. The chain includes AI algorithms that support smart contracts, which means anyone can use Cortex to add AI to their smart contracts. It also creates an incentive mechanism for collective collaboration, allowing anyone to submit and optimize models in Cortex, while model contributors can also be rewarded. The end result of Cortex, according to the whitepaper, is the creation of “artificial general intelligence”, or AGI, “being born on the Cortex”. Cortex completed a private token sale in February/March 2018 for its CTXC tokens. That funding round was led by Bitmain and FBG Capital, among other well-known investors in the cryptocurrency space. Placing artificial intelligence systems on the blockchain isn’t a straightforward process. However, Cortex will solve this problem by allowing machine learning researchers around the world to upload well-trained corresponding data models to the storage layer of the Cortex public chain. Other users who need these AI models can make inferences using the models, then pay the person who developed those models. At each inference, a full node synchronizes the model and the data from the storage tier to the local site. Making an inference using Cortex’s unique virtual machine, or CVM, will synchronize the results to the whole network and then return the result. Every time a user initiates a transaction on the Cortex, opens a smart contract, or performs an intelligence inference, the user will need to pay a certain number of “Endorphin” tokens. Endorphin is the pricing unit for transactions on Cortex. However, the platform will have two tokens, including Endorphins and Cortex Coins (CTXC). The overall goal of Cortex is to provide state-of-the-art machine learning models on the blockchain where users can infer using smart contracts. Cortex also seeks to create a machine learning platform where users can post tasks on the platform or submit artificial intelligence-based decentralized apps. Cortex’s token sale began with a single private placement round. That round took place from February 7 to March 7, 2018, during which tokens were sold at a price of 1 ETH = 1500 CTXC. In March 2018, the company announced that it had reached its target cap of 40,000 ETH for 60 million CTXC, or 20.01% of the total token distribution. FBG Capital and Bitmain were lead investors during the token sale. CTXC tokens are ERC20 tokens on the Ethereum blockchain. There’s a total supply of 299,792,458 tokens. Of the total supply, 50.03% (150 million) are reserved for Cortex coin miners as a mining reward, 24.95% (74,792,458) are dedicated to the project’s foundation from the genesis block (including 15.01% to the Cortex Lab, 9.01% to project marketing, and 0.93% to challenge bounties), with the remaining 5% going to advisors, academia, and the community from the genesis block. Cortex aims to place advanced artificial intelligence systems on the blockchain. The company recently completed a private investment round during its token sale for CTXC tokens in February/March 2018. The next step is to roll out the Cortex public chain. Key features of the platform include its smart AI contracts and its Cortex Virtual Machine, both of which allow for advanced AI-based smart contract programming.
SingularityNET is a decentralized marketplace for Artificial Intelligence (AI). The business value of AI is becoming clearer each day; however, there’s a significant gap between the people developing AI tools (researchers and academics) and the businesses that want to use them. Most organizations need a more customized solution than what a single AI project can offer, and research projects oftentimes have trouble accessing a large enough data set to build effective machine learning. SingularityNET closes these gaps. The long-term vision of the SingulairtyNET team is to build a network of complex AI Agent interactions primarily using resources from the OpenCog Foundation. To look at this further, let’s check out their in-house built humanoid robot, Sophia. Sophia uses a combination of AI Agents that range from natural language processing to physical motor controls to operate. You tell Sophia to summarize a video that’s embedded in a webpage. To do this, Sophia sends a request to Agent A. Through its AI, Agent A knows that Agent B specializes in analyzing and transcribing video while Agent C specializes in summarizing text. Agent A pays Agent B and Agent C to perform these tasks while Sophia pays Agent A to coordinate. All the while, each Agent has updated their own AI with the network information gained from these tasks and combines it with their previous experiences and knowledge. Therefore, the collective AI of the system grows at a faster rate than any individual Agent. SingularityNET wants to build a decentralized protocol for creators and users of AI to interact with each other, to not only help individual projects benefit by leveraging the strengths of other AI systems that might handle certain tasks better, but ultimately to develop SingularityNET into a functioning AI system itself, with nodes on the network making their own decisions about how to connect services and proactively provide solutions to academic and business problems. Tokenizing the network creates an AI marketplace where AI developers and sellers can not only link with others who might assist in building more robust AI solutions, but also allow AI services and products to be bought and sold, creating revenue and establishing price points where none have existed before. The SingularityNET team boasts 50+ AI developers and 10+ PhDs. Dr. Ben Goertzel leads the group as CEO and Chief Scientist. He’s also the Chairman of the OpenCog Foundation and the Artificial General Intelligence Society, as well as the Chief Scientist at Hanson Robotics, the partner company helping bring SingularityNET to life. Dr. David Hanson, founder of Hanson Robotics, serves as the Robotics Lead. Most famously, Hanson Robotics built Sophia, the most expressive humanoid robot to date. Sophia is also a proud member of the SingularityNET team. The team recently released the alpha version of the platform and is planning on launching a public beta sometime in the middle of 2018.