This time I bring you projects in the AI ​​sector. As you all know, the next round of bull market will be either DeFi RWA or artificial intelligence.

When everyone is planning for the bull market, don't focus on one track. After all, no one can predict who will fire the first shot in the bull market.

The Gensyn I will introduce this time will be in the AI ​​sector. Why? Please listen to me introduce the project. First-hand information, resources: hxsq808

What is Gensyn?

https://www.gensyn.ai/

Official Website

Gensyn is a distributed computing network for training AI models. The network uses blockchain to verify that deep learning tasks have been executed correctly and trigger payments through commands. It directly rewards supply-side participants for committing computing time to the network and performing ML tasks. The protocol does not require administrative oversight or enforcement, but rather facilitates task allocation and payments programmatically through smart contracts.

Gensyn Protocol?

The Gensyn Protocol is a layer 1 trustless protocol for deep learning computations that directly and immediately rewards supply-side participants for committing computation time to the network and performing ML tasks. As mentioned above, the fundamental challenge in building this network is verifying the machine learning work that has been completed. This is a highly complex problem that involves the intersection of complexity theory, game theory, cryptography, and optimization.

A simple solution is to check the honesty of workers by redoing their work. At a minimum, this requires doubling the required operations ("single replication"); however, even with replication, the trust problem remains unless the verifier is the actual requestor of the work (in which case they are not requesting the work because they are just performing it themselves). Therefore, ensuring the honesty of the verifier can produce an infinite chain of replication, where each new verifier needs to check the work of the previous verifier.

Financing

Gensyn has completed two rounds of financing in total. The first round took place on March 21, 2022, led by Eden Block and followed by Galaxy Digital, CoinFund, Maven11, Hypersphere Ventures, Zee Prime Capital, Entrepreneur First, Jsquare, Counterview Capital, 7percent Ventures, and Id4 Ventures, with a total investment of US$6.5 million.

The second time occurred on June 11, 2023. This time it was led by a16z and followed by many institutions including CoinFund, Canonical Crypto, Protocol Labs, Eden Block, Jsquare, M31 Capital, Zee Prime Capital, Maven11, Id4 ventures, and anand iyer. The scale of this financing was as high as 43 million US dollars.

The second round of financing made a16z more optimistic about the development of the project. On August 26, Jeff Amico, a token economics researcher at a16z, announced that he had joined the portfolio company Gensyn as the director of operations to help Gensyn cope with the operational and legal challenges brought about by the creation of a new computing infrastructure.

Mainnet

After successfully launching a parachain on the Kusama relay chain, the next phase will be to launch the final live parachain on the Polkadot relay chain. This phase will include launching the mainnet utility token, which will become the primary utility token for the protocol. The mainnet will be a hardened live protocol for full use by any organization or individual. Features or changes will be iterated through testnets and canarynets before launching on the mainnet.

ecosystem

The Gensyn protocol will become a base layer for ML computations, similar to Ethereum for smart contract execution. Going forward, we expect others to build on top of the protocol to provide rich user experiences and specific functionality in numerous niches. We expect this emerging ecosystem to start with *knowledge-based applications, allowing non-* to build and deploy ML solutions using abstractions similar to existing Web2 solutions such as Amazon’s SageMaker and DataRobot.

In addition to human knowledge in model design, there are three fundamental problems that slow progress in applied ML:

Gensyn solves the first problem by providing on-demand access to globally scalable computing at fair market prices. The Gensyn Foundation will seek to encourage solutions to the second and third problems through research, grants, and collaboration with other protocols.

Long-term vision

The Gensyn protocol will enable anyone to train ML models for any task using a self-organizing network that encompasses all existing sources of computing power.

As Web3 Dapps grow in complexity and infrastructure requirements, they are forced to fall back to Web2 where Web3 resources do not exist. By decentralizing ML computation, the Gensyn protocol brings an important infrastructure component to Web3 — reducing reliance on Web2 and further strengthening and decentralizing the entire ecosystem.

Deep learning has demonstrated incredible generalization capabilities and looks set to play a major role in the future of ML. Base models trained on the Gensyn protocol will be decentralized and globally owned — allowing humanity to equally benefit from collaborative ML development and training. Building on these base models using fine-tuning will be as simple as defining a task and paying a fair market price for the fine-tuning work — removing barriers that currently exist.

For decades, ML has advanced in both academic and industrial settings. The Gensyn protocol connects these silos through a common infrastructure with decentralized ownership, enabling all of humanity to rapidly explore the future of AI together as equal pioneers. Combining this network with hierarchical training and collectively owned base models provides a path to truly achieving AGI - the next step for humanity.

Project Benefits

This project is fully supported by a16z, which provides both financial and human resources. With the participation of a16z personnel, the upper limit of project operation and product strength has been raised.

The project has ample financial support, especially the second financing event led by a16z for US$46 million. The institution also valued the project at US$240 million. The amount of financing will be very large for R&D investment and operating costs during the development phase, which also gives a higher upper limit to the target price of the project.

Betting on the future of the AI ​​sector, the narrative of AI will never stop. Now the AI ​​sector is developing very rapidly, and the innovation of updates, iterations and new technologies is fleeting, so the AI ​​sector with strong narrative is the bright spot at present.

a16z said that recent advances in artificial intelligence are incredible and have the power to save the world. But building AI systems requires deploying greater computing power to train and reason about today's newest and most powerful models. This means that large technology companies have an advantage over startups in the race to extract value from artificial intelligence, thanks to privileged access to computing power and economies of scale in large data centers. To compete on a level playing field, startups need to be able to affordably use their own large-scale computing power.

The advantages of choosing Polkadot's three networks and developing for different networks in three different stages will help AI projects to optimize metadata for probabilistic verification of machine learning training, perform * verification of deterministic machine learning work proven on the chain, and parallelize machine learning models on heterogeneous hardware with latency constraints. There are more considerations for deploying development nodes.

Summarize#

The narrative that the AI ​​sector has become a bull market has become a fact, and Gensyn itself is developing algorithms for ChatGPT. With the iteration of ChatGPT, computing power companies like Gensyn will also be used. This time, Gensyn has also brought about technological changes, which can increase computing power by 10 times or even 100 times. You must know that today's ChatGPT can answer questions within a few seconds. If it is increased by ten times or even a hundred times, it will reach a terrifying state.

Of course, fast computing speed is definitely not its only advantage. Its best feature is that it can greatly reduce computing costs.

The cost of a single GPT-3 training in 2020 is about $12 million, more than 270 times higher than the estimated cost of GPT-2 training in 2019, which is about $43,000. In general, the model complexity (size) of the best neural networks currently doubles every three months. The hourly cost of Gensyn's machine learning training work is about $0.4, which is much lower than the cost required by AWS ($2) and GCP ($2.5). Gensyn wants to use technologies such as blockchain to implement a decentralized large-scale distributed deep learning *computing protocol with probabilistic learning proof and cryptocurrency incentive mechanism.

This time our company has also secured a large amount of quota for everyone. The most important thing is that after communicating with the institutions, there will be no lock-in of positions this time!