Let’s look out for the top most valuable machine learning funding for millions of dollars
Machine learning is a field of artificial intelligence that helps machines learn to analyze data the way humans do. ML models play a vital role in digitally transforming a business. SMBs, SMEs, and large enterprises hire offshore ML companies to adopt the data-driven models and revamp their existing systems. Let’s look out for the top most valuable machine learning funding to inspire current ML startups for millions of dollars of ML investment.
Inflection AI: The company has received one of the top artificial machine learning funding worth US$225 million. It is known as the machine learning and AI start-up. It has received US$225 million from venture capitalists in equity financing. This ML investment will lead to advancements in machine learning to make intuitive human-computer interfaces possible in the nearby future.
Evinced pushes: The company is continuing this shift left mentality with $38 million in new funding that it plans to put to work making it elementary to design for accessibility. It is on a mission to make as many web properties accessible as possible, and to do that means getting that work done as early as possible.
The OPC: It is proud to announce the new research and awareness projects funded as part of its 2022-2023 Contributions Program. Following the evaluation process, 11 projects were selected to receive funding support totaling $500,000. That project will look at privacy, artificial intelligence, and machine learning through a rural, remote and Indigenous lens.
Meet Pachama: An AI technology platform that uses satellite data and machine learning to help companies achieve net-zero or carbon neutrality to support reforestation. Pachama has acquired $55 million in Series B funding for its tech-focused carbon credit platform.
Ivy Homes: Bengaluru-based prop-tech startup Ivy Homes, which uses AI and ML to provide instant liquidity to home sellers, will use the funds to build its product and expand its team. It raised $5.75 million in equity and $1.3 million in debt in its seed round, which saw participation from Khosla Ventures, Venture Highway, Y Combinator, GFC, Fundamental, Better Capital, Titan Capital, and Rebright Partners.
LogRocket: It launches conditional recording to empower software teams to surface digital insights intelligently; the company secures $25 million in series C funding. The company expects to double the number of sessions monitored in 2021 to more than 3.5 billion sessions in 2022, comprising over 300 billion interactions, across its customer base.
Lightning AI Inc: It sells a commercial version of PyTorch Lightning, an open-source neural network development tool created by co-founder and Chief Executive Officer William Falcon. It has secured $40 million in funding from a group of investors led by Coatue. Maintaining infrastructure can require a significant amount of manual work, which slows down machine learning projects.
Vamstar: The AI-enabled global sourcing and procurement platform for medical supplies and pharmaceuticals, has closed a $9.5m Series A funding round. Vamstar combines functionality for streamlining healthcare sourcing and procurement processes by using machine learning, deep learning, and natural language processing to connect billions of data points across the supply chain network, provide real-time market intelligence, and enable digital commerce through a common e-procurement platform.
Vahak: It startup transport services marketplace Vahak. It has raised $14 million in a funding round led by Nexus Venture Partners. The funds will be used for rapid user-base expansion, building a tech infrastructure by incorporating artificial intelligence, machine learning, big data, and providing additional value-added services.
Synaptic: It is a leading alternative data insights start-up, said it has raised $20 million in a Series B funding round led by Valor Equity Partners. Synaptic combines machine learning, and finance to bring sophisticated alternative data insights to decision-makers.
Source: analyticsinsight.net
