Blockchain and AI technologies are both disruptive to the digital environment, and sometimes toward each other. More important, they also have a synergistic effect when combined.
Disruption is characterized by new efficiency, security and trust. Companies that stick with outdated technologies inevitably become dinosaurs, while those that adopt new tools can evolve and be successful. By looking ahead, you’ll have plenty of opportunities to profit while riding the waves of disruption.
Blockchain technology helps AI learn faster about emerging and evolving security threats. For example, retailers and loss-prevention specialists can use blockchain-enhanced AI techniques to more quickly analyze shoplifting or employee thefts in multiple locations at different times.
Also, real-time object recognition in video data is now emerging as a refinement beyond simple photo recognition in AI algorithms. Similar to the development of automated license plate reader (ALPR) technologies, this blockchain-fueled video-recognition boom should lead to a new round of development for apps to help us quickly connect names with faces in grainy videos taken by phones. If you’re an app developer with a talent for social media, now’s the time to start thinking about how to use on-the-fly facial recognition in your work.
Blockchain is energy-intensive, especially when mining coins. Yet, AI could dramatically reduce the carbon footprint as well as maintenance costs. That’s because AI improves operating efficiencies. More efficient blockchain practices can help reduce latency and optimize the mining load.
The main benefits of blockchain are permanency and visibility of records, especially for financial transactions. Transparency breeds trust. Applying blockchain methods to enhance AI processes means users, researchers and regulators can follow clear pathways to discover exactly how a process occurred, and how to improve it.
Artificial intelligence technologies are already disrupting old paradigms in healthcare, customer service, security, manufacturing, gaming, and even agriculture. Blockchain technologies are also disruptive, and they’ve already brought plenty of change to financial services and trading industries.
Reduce system risks
By using AIs coded for a DAO using specified smart contracts, developers can ensure that only those actions are performed. This can greatly reduce the risk of catastrophic system failure.
Storing & using sensitive data
A blockchain is the ideal way to store sensitive data. As AI-enhanced blockchain technologies make personal and private data more secure, they also lead to new ways to harvest, sell and use that data.
Lowering barriers to entry
Going forward, more and more data will be available to consumers and businesses through a blockchain structure. The processes required to grant access and track data are a job best left to intelligent systems, which means AI will always be part of the blockchain environment.
Blockchain technology is already disrupting the AI services marketplace to the extent that smaller tech players are able to use machine learning at lower cost. These lower barriers to entry have two disruptive effects – Wider access to data by small players, and easier monetization of AI applications by independent developers.
New market opportunities
Innovative marketers are already using blockchain-powered AI to find and focus on their best customers, just as medical researchers use similar methods to identify promising new pharmaceuticals. Combined, these technologies help screen sales leads faster and better, so click-throughs and closing ratios are higher.
Give AI results more credibility & effectiveness
One of the biggest issues for users of AI systems is to understand what happens inside the “black box.” Blockchain can help humans better understand AI decision-making processes as well as the results they provide. Since a blockchain will faithfully record the trail of decisions in the form of data points for each event, it’s easy to audit results later.
A clear audit trail through the entire transaction makes the data more trustworthy as well as providing a way to trace the machine-learning process. Better auditing trails will improve the effectiveness of AI, and secure data sharing supports better models leading to improved results.
Blockchain transparency brings more credibility to transactions, and AI allows the development of artificial trust between systems. Going forward, trust verification tasks will be increasingly managed by AI virtual agents that learn to trust each other based on blockchain credentials.
Along with trust-building through increased machine-to-machine collaboration, AI-enhanced blockchain is also a solution for Quorum applications and multiple-agent scenarios. Of course, trust-building and collaboration are the keys to success for any project involving swarm robotics. If you’re a developer for drone apps, now’s the time to start thinking about how to choreograph an entire fleet of them. .
At the intersection of blockchain and AI
After several years of parallel development, it looks like blockchain is beginning to disrupt the speed and direction of AI development itself. We’re quickly approaching a convergence where the synergy between blockchain and AI technologies could lead to even better results.
Although there are many blockchain startups, only a few are positioned at the intersection with AI. Let’s survey the development landscape to see how blockchain is disrupting the AI industry, and how you can hack that synergy.
Marketplaces for AI algorithms & services
Organizations such as SingularityNET and Synaose.ai offer a decentralized marketplace in which to buy and sell algorithms. Developers and vendor provide software or hardware in exchange for cryptocurrency, or other AI services.
Of course, this open-source marketplace supports cryptocurrency token payments in exchange for AI services. From the perspective of outside traders and investors, these buy-sell transactions are fungible because they’re based on smart contracts built using templates with standardized APIs.
Popular AI-blockchain services may include video or image processing applications, especially ones that rely on data-intensive operations to identify people or generate written texts. If you’re a developer for security apps or social media, check out platforms like Neuromation. They offer synthetic data generation and algorithm training using data to mimic reality. And, there are already AI-enhanced cameras available in the marketplace which promise better facial recognition, even while objects are moving.
Language processing services are another niche just now beginning to benefit from machine learning coupled with blockchain transparency. Translation and interpretation are ripe for new efficiencies through combined AI-blockchain technologies. Static voice recognition is already the norm, and dynamic voice recognition of groups is the next step for blockchain-enhanced AI.
Faster learning through machine competition and training
Artificial intelligence is both disruptive and synergistic for blockchain projects. That’s because an AI-powered mining algorithm can quickly improve its own ability by working alone. Yet, successful machine learning still relies on human oversight to input the right data, then follow up with good management decisions.
Platforms like TraneAI provide decentralized AI training and give users updated training downloads to help AI models better predict future results. Machines collaborate yet to compete to improve the learning process.
Crowdsourcing models for investors & traders
If you’re a trader or investor, you may already be using AI models for mechanical trading and EAs. Likewise, the platform operator is also combining the same technical indicators and features from the best-performing individual models into a single AI model.
Blockchain technologies can take traders and investors far beyond the earlier generation of predictive indicators in financial markets. Here’s an interesting way in which is disrupting AI methods: Crowdsourcing as a predictive engine for hedge funds and other investors. Blockchain-savvy investors aim to base their buying and selling decisions on which way the crowd is moving.
For example, the Numer.ai model uses a weekly competition where users can submit predictions of a given fund or index performance results for the upcoming week. Users are scored for the accuracy and consistency of their AI models’ predictions. Prizes are paid in the form of digital tokens.
Crowdz is an AI-based blockchain platform that lets business owners use commercial factoring to obtain cash from active invoices and purchase orders. So, if you’re an online business owner with outstanding accounts receivable, you can get working capital based on your AR. For credit-challenged business owners who need fast cash, Crowdz may offer a sweet end run around bankers.
BurstIQ and other recent entrants to the AI-blockchain marketplace are aiming to leverage the power of AI and blockchain to improve everything from pharmaceutical discoveries and clinical trials to patient care and insurance claims.The permanency and transparency of blockchain transactions make them ideal for documentation and regulatory compliance. With the power of blockchain-driven AI applications, precision medicine can become the norm.
Social mining is getting smarter
Social mining is another area in which blockchain and AI technologies are a potent combination – Users bring value to a community, whether in the form of content or engagement, and they’re rewarded with digital tokens. For example, Mithril gives crypto in exchange for user content, engagement and influence on social media platforms. And, Social Coin is promoted as the “currency of community action” with rewards for people who benefit their communities.
AI and blockchain are also converging with intelligent discovery apps such as Bubblo. These types of real-time discovery apps offer personalized recommendations for restaurants, bars, hotels and other venues.
Yet they’re more than just ordinary map-recommendation apps – Users are rewarded with tokens for generating data including reviews and directions. Most importantly, users can offer access to their own anonymized data in order to receive discounts and other incentives. Likewise, AI developers can use these tokens and datasets to train their own algorithms.
Disruption goes both ways – How AI will benefit blockchain
AI technologies have the potential to reduce some of the current technical limitations on blockchain, including efficiency in energy consumption, scalability, security, privacy, and data access.
Mining is energy-intensive, and AI is ideal for tasks like optimizing energy consumption and balancing loads on a network. Along with lower energy costs, AI-fueled miners should expect lower investment costs in their hardware, since operations will become more efficient.
Scalability can also be enhanced by applying AI to blockchain operations such as data sharing and federated learning, or collaborative machine learning, which lets systems learn together and exchange training materials with or without central control.
Security is another area where AI can improve blockchain operations. Although the blockchain itself is nearly impossible to hack, the surrounding layers and apps aren’t quite as secure, as we’ve learned from Bitfinex, Mt. Gox and others.
Machine learning has now reached the stage of development where it can help guarantee a secure environment for the development and deployment of security-sensitive apps. Of course, handling and ownership of personal data always creates privacy issues, and AI seems likely to provide benefits by facilitating encryption and decryption.
Better blockchain efficiency with AI
Beyond improving miners’ efficiency, AI technologies can greatly reduce the costs of validating and sharing blockchain transactions. An AI-powered system could compute on-the-fly availability as well as the likelihood that particular nodes will be the first to perform specific tasks.
This insight could be a big money-saver, since it might allow other miners the option of stopping their efforts to compete for that transaction. In any case AI should reduce network latency, which will improve overall efficiency.
The efficiency of AI also extends to blockchain hardware. Hardware miners have spent heavily on their equipment, so AI’s capability to manage and reduce energy consumption will be key to its adoption here. The next step toward large-scale efficiency is to use hardware in the form of neural nets. Some bigger miners like Bitmain are already doing this.
Blockchain and AI technologies are individually disruptive to the overall environment, and sometimes to each other. They also have a synergistic effect when combined. Whether you’re an entrepreneur, investor, trader or app developer, you’ll soon find plenty of new ways to leverage the two for best results.