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There’s a brand new king on the town: Matt Shumer, co-founder and CEO of AI writing startup HyperWrite, at this time unveiled Reflection 70B, a brand new massive language mannequin (LLM) primarily based on Meta’s open supply Llama 3.1-70B Instruct that leverages a brand new error self-correction method and boasts superior efficiency on third-party benchmarks.
As Shumer introduced in a put up on the social community X, Reflection-70B now seems to be “the world’s top open-source AI model.”
He posted the next chart displaying its benchmark efficiency right here:
Reflection 70B has been rigorously examined throughout a number of benchmarks, together with MMLU and HumanEval, utilizing LMSys’s LLM Decontaminator to make sure the outcomes are free from contamination. These benchmarks present Reflection constantly outperforming fashions from Meta’s Llama collection and competing head-to-head with prime business fashions.
You may attempt it your self right here as a demo on a “playground” web site, however as Shumer famous on X, the announcement of the brand new king of open-source AI fashions has flooded the demo website with site visitors and his staff is scrambling to seek out sufficient GPUs (graphics processing items, the dear chips from Nvidia and others used to coach and run most generative AI fashions) to spin as much as meet the demand.
How Reflection 70B stands aside
Shumer emphasised that Reflection 70B isn’t simply aggressive with top-tier fashions however brings distinctive capabilities to the desk, particularly, error identification and correction.
As Shumer instructed VentureBeat over DM: “I’ve been thinking about this idea for months now. LLMs hallucinate, but they can’t course-correct. What would happen if you taught an LLM how to recognize and fix its own mistakes?”
Therefore the identify, “Reflection” — a mannequin that may replicate on its generated textual content and assess its accuracy earlier than delivering it as outputs to the person.
The mannequin’s benefit lies in a method known as reflection tuning, which permits it to detect errors in its personal reasoning and proper them earlier than finalizing a response.
Reflection 70B introduces a number of new particular tokens for reasoning and error correction, making it simpler for customers to work together with the mannequin in a extra structured means. Throughout inference, the mannequin outputs its reasoning inside particular tags, permitting for real-time corrections if it detects a mistake.
The playground demo website consists of recommended prompts for the person to make use of, asking Reflection 70B what number of letter “r” cases there are within the phrase “Strawberry” and which quantity is bigger, 9.11 or 9.9, two easy issues many AI fashions — together with main proprietary ones — fail to get proper constantly. Our assessments of it have been gradual, however Reflection 70B finally offered the right response after 60+ seconds.
This makes the mannequin notably helpful for duties requiring excessive accuracy, because it separates reasoning into distinct steps to enhance precision. The mannequin is on the market for obtain by way of the AI code repository Hugging Face, and API entry is about to be out there later at this time via GPU service supplier Hyperbolic Labs.
An much more highly effective, bigger mannequin on the best way
The discharge of Reflection 70B is simply the start of the Reflection collection. Shumer has introduced that an excellent bigger mannequin, Reflection 405B, might be made out there subsequent week.
He additionally instructed VentureBeat that HyperWrite is engaged on integrating the Reflection 70B mannequin into its main AI writing assistant product.
“We’re exploring a number of ways to integrate the model into HyperWrite — I’ll share more on this soon,” he pledged.
Reflection 405B is anticipated to outperform even the highest closed-source fashions in the marketplace at this time. Shumer additionally mentioned HyperWrite would launch a report detailing the coaching course of and benchmarks, offering insights into the improvements that energy Reflection fashions.
The underlying mannequin for Reflection 70B is constructed on Meta’s Llama 3.1 70B Instruct and makes use of the inventory Llama chat format, making certain compatibility with present instruments and pipelines.
Shumer credit Glaive for enabling fast AI mannequin coaching
A key contributor to Reflection 70B’s success is the artificial information generated by Glaive, a startup specializing within the creation of use-case-specific datasets.
Glaive’s platform allows the fast coaching of small, extremely targeted language fashions, serving to to democratize entry to AI instruments. Based by Dutch engineer Sahil Chaudhary, Glaive focuses on fixing one of many largest bottlenecks in AI growth: the supply of high-quality, task-specific information.
Glaive’s method is to create artificial datasets tailor-made to particular wants, permitting firms to fine-tune fashions rapidly and affordably. The corporate has already demonstrated success with smaller fashions, reminiscent of a 3B parameter mannequin that outperformed many bigger open-source options on duties like HumanEval. Spark Capital led a $3.5 million seed spherical for Glaive greater than a 12 months in the past, supporting Sahil’s imaginative and prescient of making a commoditized AI ecosystem the place specialist fashions will be skilled simply for any activity.
By leveraging Glaive’s expertise, the Reflection staff was in a position to quickly generate high-quality artificial information to coach Reflection 70B. Shumer credit Sahil and the Glaive AI platform for accelerating the event course of, with information generated in hours slightly than weeks.
In whole, the coaching course of took three weeks, in line with Shumer in a direct message to VentureBeat. “We trained five iterations of the model over three weeks,” he wrote. “The dataset is entirely custom, built using Glaive’s synthetic data generation systems.”
HyperWrite is a uncommon Lengthy Island AI startup
At first look, it looks like Reflection 70B got here from nowhere. However Shumer has been on the AI sport for years.
He based his firm, initially known as Otherside AI, in 2020 alongside Jason Kuperberg. It was initially primarily based in Melville, New York, a hamlet about an hour’s drive east of New York Metropolis on Lengthy Island.
It gained traction round its signature product, HyperWrite, which began as a Chrome extension for shoppers to craft emails and responses primarily based on bullet factors, however has advanced to deal with duties reminiscent of drafting essays, summarizing textual content, and even organizing emails. HyperWrite counted two million customers as of November 2023 and earned the co-founding duo a spot on Forbes‘ annual “30 Under 30” Listing, finally spurring Shumer and Kuperberg and their rising staff to vary the identify of the corporate to it.
HyperWrite’s newest spherical, disclosed in March 2023, noticed a $2.8 million injection from traders together with Madrona Enterprise Group. With this funding, HyperWrite has launched new AI-driven options, reminiscent of turning net browsers into digital butlers that may deal with duties starting from reserving flights to discovering job candidates on LinkedIn.
Shumer notes that accuracy and security stay prime priorities for HyperWrite, particularly as they discover advanced automation duties. The platform remains to be refining its private assistant instrument by monitoring and making enhancements primarily based on person suggestions. This cautious method, just like the structured reasoning and reflection embedded in Reflection 70B, exhibits Shumer’s dedication to precision and accountability in AI growth.
What’s subsequent for HyperWrite and the Reflection AI mannequin household?
Trying forward, Shumer has even larger plans for the Reflection collection. With Reflection 405B set to launch quickly, he believes it would surpass the efficiency of even proprietary or closed-source LLMs reminiscent of OpenAI’s GPT-4o, presently the worldwide chief, by a big margin.
That’s unhealthy information not just for OpenAI — which is reportedly in search of to lift a big new spherical of personal funding from the likes of Nvidia and Apple — however different closed-source mannequin suppliers reminiscent of Anthropic and even Microsoft.
It seems that as soon as once more within the fast-moving gen AI area, the stability of energy has shifted.
For now, the discharge of Reflection 70B marks a big milestone for open-source AI, giving builders and researchers entry to a robust instrument that rivals the capabilities of proprietary fashions. As AI continues to evolve, Reflection’s distinctive method to reasoning and error correction could set a brand new customary for what open-source fashions can obtain.