The “Road to Mainnet” campaign by Neura AI Blockchain lays out a complex roadmap that is expected to propel the mainnet to success. With its smooth integration of AI, Web3, and Cloud computing, this much anticipated Layer-1 blockchain offers state-of-the-art Web3 solutions.

Neura has started a new collection on Galxe to commemorate this accomplishment and give users the chance to win a unique Neura NFT.

Neura’s strategy plan outlines how to get the Neura Network in front of development teams that are excited to explore the potential of blockchain technology. Neura AI Blockchain solves issues faced by many Web3 startups with features like an Initial Model Offering (IMO) framework and a decentralized GPU marketplace.

Web3 developers are invited to participate in the AI Innovators campaign, which Neura has launched to demonstrate its capabilities, in exchange for tempting prizes.

This developer competition aims to showcase Neura Blockchain’s AI and platform capabilities, supporting its ecosystem on the Road to Mainnet, rather than just be a competitive event.

Neura Blockchain is at the forefront of utilizing blockchain and artificial intelligence in a world where these technologies are rapidly developing. Because of its custom features that unlock the best AI features in the Web3 space, its launch in 2024 is something to look forward to.

The Road to Mainnet public testnet competition, according to Neura, will highlight important Web3 features like improving the effectiveness of deploying and running AI models, encouraging user participation, and creating a positive network effect among these overlapping technologies.

The Phi-3 Mini, the first of three lightweight models from Microsoft, is the company’s smallest AI model to date.

Microsoft is exploring models that are trained on smaller-than-usual datasets as an increasing number of AI models enter the market. According to The Verge, Phi-3 Mini is now available on Hugging Face, Ollama, and Azure. It has 3.8 billion parameters, or the number of complex instructions a model can understand. Two more models are planned for release. Phi-3 Medium and Phi-3 Small measure 14 billion parameters and seven bullion parameters, respectively. It is estimated that ChatGPT 4 contains more than a trillion parameters, to put things into perspective.

Released in December 2023, Microsoft’s Phi-2 model has 2.7 billion parameters and can achieve performance levels comparable to some larger models. According to the company, Phi-3 can now perform better than its predecessor, providing responses that are comparable to those that are ten times larger.

Benefits of the Phi-3 Mini

Generally speaking, smaller AI models are less expensive to develop and operate. Because of their compact design, they work well on personal computers and phones, which facilitates their adaptation and mass market introduction.

Microsoft has a group devoted to creating more manageable AI models, each with a specific focus. For instance, as its name would imply, Orca-Math is primarily concerned with solving math problems. T.

There are other companies that are focusing on this field as well. For example, Google has Gemma 2B and 7B that are focused on language and chatbots, Anthropic has Claude 3 Haiku that is meant to read and summarize long research papers (just like Microsoft’s CoPilot), and Meta has Llama 3 8B that is prepared to help with coding.

Although smaller AI models are more suitable for personal use, businesses may also find use for them. These AI models are ideal for internal use since internal datasets from businesses are typically smaller, they can be installed more quickly, are less expensive, and easier to use.

A study published on Monday found that tech behemoths like Google, Nvidia, and Huawei are using Artificial Intelligence (AI) models to revolutionize weather forecasting.

The study shows how AI-powered weather prediction models can quickly and accurately predict the trajectory and intensity of major storms. It was published in the esteemed journal npj Climate and Atmospheric Science. According to researchers, these AI-based forecasts are quicker, less expensive, and require less processing power than traditional approaches while maintaining the same level of accuracy.

The Storm Ciaran that devastated northern and central Europe in November 2023 is the subject of the research, which is headed by Professor Andrew Charlton-Perez. Using cutting-edge AI models created by Google, Nvidia, and Huawei, the team analyzed the behavior of the storm and compared their results with more conventional physics-based models.

Remarkably, the AI models accurately forecasted the storm’s rapid intensification and trajectory up to 48 hours in advance. According to the researchers, the forecasts were nearly identical to those generated by conventional methods.

“AI is transforming weather forecasting before our eyes,” said Professor Charlton-Perez. Weather forecasts two years ago hardly ever used modern machine learning techniques. These days, a number of our models can generate 10-day global forecasts in a matter of minutes.”

The study emphasizes how well the AI models can represent key atmospheric parameters that influence a storm’s development, such as how a storm interacts with the jet stream, a slender channel of powerful high-level winds.