The increasing penetration of renewable energy sources in day-ahead energy markets introduces challenges in balancing supply and demand, ensuring grid resilience, and maintaining trust in decentralized trading systems. This paper proposes a novel framework that integrates the Proximal Policy Optimization (PPO) algorithm, a state-of-the-art reinforcement learning method, with blockchain technology to optimize automated trading strategies for prosumers in day-ahead energy markets. We introduce a comprehensive framework that employs a Reinforcement Learning (RL) agent for multi-objective energy optimization and blockchain for tamper-proof data and transaction management. Simulations using real-world data from the Electricity Reliability Council of Texas (ERCOT) demonstrate the effectiveness of our approach. The RL agent achieves demand-supply balancing within 2% of the demand and maintains near-optimal supply costs for the majority of the operating hours. Moreover, it generates robust battery storage policies capable of handling variability in solar and wind generation. All decisions are recorded on an Algorand-based blockchain, ensuring transparency, au-ditability, and security - key enablers for trustworthy multi-agent energy trading. Our key contributions are a novel system architecture, the use of curriculum learning to train the RL agent, and policy insights that support real-world deployment.

Welcome to MATRIX AI Network. Matrix AI Network was founded in 2016 with a team of young professionals who dare to think big while no bow to failures. Not just with dreams, the Team rolls up sleeves to design and build with persistency, unlike many others. We are not perfect but we are getting better. The Matrix 1.0 blockchain platform is the first AI-optimised blockchain platform.

Today is the 28th of June. As usual we are having this June AMA with our CEO Mr. Owen Tao. And just for your information, Owen has just been released from a 17 days quarantine because he has been identified as a cross contact, and as a result of visiting a shopping mall. So why don't you, Owen, share with us what's the life like being quarantined in a hotel, is it a hotel? So the environment is good, yeah?

Artificial Intelligence (AI): The theory and development of computer systems that can perform tasks -- often using natural language processing (NLP), machine learning and natural language understanding (NLU) -- that normally require human intelligence, comprehension and understanding. Augmented Reality (AR): Technology, using involving glasses, visors, goggles or smartphones, that superimposes a computer-generated image on a user's view of the actual world, providing a composite view that often includes perceptual information. Avatar: A computerized icon or figure which represents a person, pet or entity in video games, internet forums, games, chat rooms, virtual reality and other channels. Block: A place in a blockchain where data is stored and encrypted. Blockchain: A shared, immutable digital ledger that records and maintains transactions and tracks assets across a peer-to-peer business network. Bitcoin: A decentralized, digital cryptocurrency that doesn't rely upon a central bank or trusted source which can be transferred from user to user on a peer-to-peer network using blockchain technology.

Deep neural networks (DNNs) could be very useful in blockchain applications such as DeFi and NFT trading. However, training / running large-scale DNNs as part of a smart contract is infeasible on today's blockchain platforms, due to two fundamental design issues of these platforms. First, blockchains nowadays typically require that each node maintain the complete world state at any time, meaning that the node must execute all transactions in every block. This is prohibitively expensive for computationally intensive smart contracts involving DNNs. Second, existing blockchain platforms expect smart contract transactions to have deterministic, reproducible results and effects. In contrast, DNNs are usually trained / run lock-free on massively parallel computing devices such as GPUs, TPUs and / or computing clusters, which often do not yield deterministic results. This paper proposes novel platform designs, collectively called A New Hope (ANH), that address the above issues. The main ideas are (i) computing-intensive smart contract transactions are only executed by nodes who need their results, or by specialized serviced providers, and (ii) a non-deterministic smart contract transaction leads to uncertain results, which can still be validated, though at a relatively high cost; specifically for DNNs, the validation cost can often be reduced by verifying properties of the results instead of their exact values. In addition, we discuss various implications of ANH, including its effects on token fungibility, sharding, private transactions, and the fundamental meaning of a smart contract.

As businesses, governments and consumers rely on digital systems to fulfil most of their daily operations, so do the risks of those systems being hacked increase. The more the technologies they adopt, the greater the hazards they have to face. In fact, new solutions to ease businesses daily operations such as Artificial Intelligence in Operative Systems and IT software huge databases, bring even more complexity to an already convoluted world. However, these new techs can also become their strongest allies! If properly developed and embraced, they can deliver new layers of security that build up a strong shield of protection against hackers.

Anchor Neural World blockchain platform, is receiving increasing support from Japan's investment holdings and high-tech companies around the world. The recent strategic partnership agreement between Anchor Value (that invested in ANW blockchain platform) and the Shenzhen Drone Manufacturers Association (Shenzhen UAV Industry Association) has attracted attention not only from specialists but also from the major Japanese media. Publications in SANSPO, ASAHI, NICOVIDEO and DREAM NEWS highlighted not only the potential of artificial intelligence in the management and opportunities provided by blockchain technologies but also the uniqueness of ANW artificial intelligence engine, which can be used with maximum efficiency in any of spheres from finance to education. The visibility and recognisability of the ANW platform is already increasing according to the principle of a snow bowl: as companies join the project, its development becomes more powerful, which increases the attractiveness of the platform for innovative business.

Organizations are increasingly looking to adopt blockchain technologies for alternative data storage. And with heaps of data distributed across blockchain ledgers, the need for data analytics with AI is growing. The combination of AI and blockchain is fueling the onset of the "Fourth Industrial Revolution" by reinventing economics and information exchange. From healthcare to government, the potent combination of both AI and blockchain is slowly but surely transforming industries. Google DeepMind is developing an "auditing system for healthcare data".

IBM this week launched a new supply chain service based on its blockchain platform and open-source software from recently-acquired Red Hat that allows developers and third-party apps to integrate legacy corporate data systems onto a distributed ledger. Through the use of open APIs, the new Sterling Supply Chain Suite allows distributors, manufacturers and retailers to integrate their own data and networks – as well as those of their suppliers – onto a Hyperledger-based blockchain to track and trace products and parts. Among the data that can be integrated are IoT sensor systems for real-time shipment position location. "This is the first move from IBM in what we anticipate to be a significant investment in the reinvention of supply chains by global organizations in the coming decades," an IBM spokesperson said via email. The "As a Service" model delivers services, not products; flexibility, not rigidity; and costs that align to business outcomes.

At ROSS, we're always talking to lawyers about how artificial intelligence is changing their practice. Our discussions are usually focused on AI and legal research. But sometimes the conversation turns to applications that might have seemed far-fetched a couple of years ago but now don't seem quite so crazy. A recent conversation with plaintiff's personal injury lawyers turned toward the application of prediction markets to settlement negotiations. The gist of the idea was that crowd-sourced predictions on settlement amounts could move unreasonable parties into reasonable settlement range. Although the theory that prediction markets could assist in litigation settlement has been around for awhile, it hasn't gained much practical traction.