Reflection AI Emerges with $130M Funding to Pursue Superintelligent Autonomous Coding Systems

Superintelligence startup Reflection AI launches with $130M in funding - SiliconANGLE

Superintelligence startup Reflection AI launches with $130M in funding Reflection AI Inc., a new startup led by former Google DeepMind researchers, launched today with $130 million in funding. The company raised the capital over two rounds. The first, a $25 million seed investment, was led by Sequoia Capital and CRV. The latter firm also co-led the subsequent $105 million Series A raise with Lightspeed Venture Partners. Reflection AI's funding rounds drew other high-profile backers as well. Its investors reportedly include Nvidia Corp.'s venture capital arm, LinkedIn co-founder Reid Hoffman and Scale AI Inc. Chief Executive Officer Alexandr Wang. The company is valued at $555 million. Reflection AI is led by co-founders Misha Laskin (right) and Ioannis Antonoglou (left). Laskin, the company's CEO, helped develop the training workflow for Google LLC's Gemini large language model series. Antonoglou worked on Gemini's post-training systems. Post-training is the process of optimizing an LLM after it's trained to boost output quality. Reflection AI is seeking to develop so-called superintelligence, which it defines as an artificial intelligence system capable of performing most work that involves a computer. As an initial step towards that goal, the company is building an autonomous programming tool. Reflection AI believes the technical building blocks necessary to create such a tool can be repurposed to build a superintelligence. "The breakthroughs needed to build a fully autonomous coding system -- like advanced reasoning and iterative self-improvement -- extend naturally to broader categories of computer work," Reflection AI staffers wrote in a blog post. Initially, the company will focus on developing AI agents that automate relatively narrow programming tasks. Some agents will focus on scanning developers' code for vulnerabilities. Others will optimize applications' memory usage and test them for reliability issues. Reflection AI also plans to automate a number of adjacent tasks. According to the company, its technology can generate documentation that explains how a particular snippet of code works. The software will also help manage the infrastructure on which customer applications run. According to a job posting on Reflection AI's website, the company plans to power its software using LLMs and reinforcement learning. Historically, developers trained AI models on datasets in which each data point was accompanied by an explanation. Reinforcement learning removes the need to include such explanations, which makes it easier to create training datasets. The job posting also reveals Reflection AI plans to "explore novel architectures" for its AI systems. That suggests the company might look beyond the Transformer neural network architecture that underpins most LLMs. A growing number of LLMs use a competing architecture called Mamba that is more efficient in certain respects. Another job posting, for an AI infrastructure expert, suggests that Reflection AI plans to train its models using up to tens of thousands of graphics cards. The company also detailed it will work on "vLLM-like platforms for non-LLM models." Developers use vLLM, a popular open-source AI tool, to reduce the memory usage of their language models. "As the team advances model intelligence to increase its scope of capabilities, Reflection's agents take on more responsibilities," Sequoia Capital investors Stephanie Zhan and Charlie Curnin wrote in a blog post. "Imagine autonomous coding agents working tirelessly in the background, handling workloads that slow teams down."

Reflection AI Raises $130 Million to Build Autonomous Coding Systems | PYMNTS.com

Artificial intelligence (AI) startup Reflection AI emerged from stealth Friday (March 7), saying it is focused on building autonomous coding systems. "At Reflection, we're building superintelligent autonomous systems," the company said in a Friday post on LinkedIn. "We believe that solving autonomous coding will enable superintelligence more broadly." Reflection aims to build tools that are fully autonomous, rather than being co-pilots or assistants, and to develop superintelligence, which is AI that is smarter than most humans, the report said. The company already has paying customers in financial services, technology and other sectors that have large coding teams, per the report. Sequoia said in a Friday blog post that coding assistants already help developers increase their speed and productivity tenfold and that autonomous coding agents are the next leap forward. "Reflection's autonomous coding agents integrate directly into an organization's codebase and engineering workflows, and autonomously tackle well-scoped engineering tasks entirely end-to-end," Sequoia's post said. "They read, write, test and deploy code, handling all the infrastructure on your behalf, relieving the burden of entire engineering workloads from developers and teams." CRV said in a Friday blog post that the technology Reflection is building "has the potential to redefine industries." "Imagine a world where engineering teams can tackle their backlogs in days instead of months, where code migrations happen seamlessly and where cyber vulnerabilities are remediated before they become critical," CRV's post said. "This is the world Reflection AI is building." Lightspeed said in a Friday blog post that Reflection AI's approach to scaling the autonomous capabilities of large language models (LLMs) with reinforcement learning (RL) brings AI closer to superintelligence. "Their system can plan, debug and execute complex programming tasks autonomously -- a leap forward that positions Reflection AI as a major player in the future of intelligent software engineering and beyond," the Lightspeed post said.

Reflection AI launches after securing $130 million in funding By Investing.com

Investing.com -- Reflection AI, a startup founded by former Google DeepMind researchers Misha Laskin and Ioannis Antonoglou, has secured $130 million in funding. The company is focused on developing superintelligent autonomous systems, starting with autonomous coding. Laskin and Antonoglou, who were instrumental in leading reinforcement learning for Alphabet (NASDAQ:GOOGL) Inc.'s AI unit's model, Gemini, have now turned their attention to building coding agents that can operate independently. The duo believes that solving autonomous coding will pave the way for broader superintelligence. In a statement on X, Laskin outlined the three defining aspects of Reflection AI: a team experienced in creating advanced RL and LLM systems, a commitment to building the best autonomous coding systems globally, and an equal focus on research and product. He emphasized that superintelligence cannot be developed in isolation. Reflection AI has been operating under the radar until now, announcing its new funding. The funding comprises a $25 million seed funding round led by Sequoia Capital and CRV, and a $105 million Series A round led by Lightspeed Venture Partners and CRV. The list of investors includes Reid Hoffman, co-founder of LinkedIn, Scale AI CEO Alexandr Wang, SV Angel, and the venture capital branch of Nvidia Corp . (NASDAQ:NVDA) After the latest funding round, the startup's valuation stands at $555 million.

Ex-DeepMind Researchers' New Startup Aims for Superintelligence

Two top researchers from Google's artificial intelligence lab DeepMind have raised $130 million for a new company with the goal of achieving superintelligence through AI-powered coding agents capable of self-direction. The startup, Reflection AI, has so far been operating under the radar. It plans to emerge from stealth on Friday with the announcement of its new funding, which includes a $25 million seed funding round led by Sequoia Capital and CRV, as well as a $105 million Series A round led by Lightspeed Venture Partners and CRV.