Microsoft has finally found what it believes is the perfect partner to begin training its artificial intelligence (AI) models on – Aptos Labs, a layer-1 blockchain company building a ChatGPT-powered chatbot called “Aptos Assistant” .
As part of the collaboration, Microsoft’s AI models will be trained using blockchain data verified by Aptos, while Aptos will also use Microsoft’s Azure Cloud to run its validation nodes that will hopefully improve the reliability and security of its services will improve.
Aptos Labs, which recently raised $350 million in funding from investors, according to Crunchbase, supports up to 160,000 transactions per second, competing with other networks including Avalanche, Solana and Bitcoin. When Microsoft invested $10 billion in OpenAI in 2019, it sent a strong signal to big tech about the need to quickly adapt, transform and integrate.
But even before ChatGPT’s boom, Microsoft was already one step ahead in trying to address the reality that future AI technology would naturally produce biased misinformation while posing serious privacy and security risks. In 2018, the tech giant set up its AI red team, made up of interdisciplinary experts tasked with exploring the risks these future AI models would pose by stepping into the shoes of these black hatters and trying to systems to operate.
AI + Web3
Daniel An, Microsoft’s global director of business development for AI and Web3, said TechCrunch+ that AI will be brought into these next-gen solutions on a larger scale in the coming months. Aptos Labs co-founder and CEO said so too TechCrunch that the main focus for both companies is to solve the problems of the respective industries.
“We can become incredibly efficient at using these tools every day in our lives,” Shaikh said. “Whether it’s finding and compiling an index of the best restaurants in your area or helping you write code for your work or research.”
In efforts to foster a more transparent ecosystem of these AI-generated outputs and content production, those harder questions need to be asked about how to determine if these outputs are truly authentic, free from human bias that is intrinsically rooted in most of these algorithms that we’ve seen to date. Unfortunately, the models the public has been exposed to are full of biases and what experts call “hallucinations,” which very often fabricate facts or scenarios that never actually existed.
With US lawmakers calling on Congress to pass a basic framework governing ethical AI use, the opportunity for these AI applications and integrations remains limited. For the first half of 2023, AI startups have raised about $25 billion which really sets the stage of priority compared to this crypto boom which also faces similar challenges regarding its regulation and classification in the financial industry.
