Diffusion models achieve high-quality image generation but are limited by slow iterative sampling. Distillation methods alleviate this by enabling one- or few-step generation. Flow matching, originally introduced as a distinct framework, has since been shown to be theoretically equivalent to diffusion under Gaussian assumptions, raising the question of whether distillation techniques such as score distillation transfer directly. We provide a simple derivation -- based on Bayes' rule and conditional expectations -- that unifies Gaussian diffusion and flow matching without relying on ODE/SDE formulations. Building on this view, we extend Score identity Distillation (SiD) to pretrained text-to-image flow-matching models, including SANA, SD3-Medium, SD3.5-Medium/Large, and FLUX.1-dev, all with DiT backbones. Experiments show that, with only modest flow-matching- and DiT-specific adjustments, SiD works out of the box across these models, in both data-free and data-aided settings, without requiring teacher finetuning or architectural changes. This provides the first systematic evidence that score distillation applies broadly to text-to-image flow matching models, resolving prior concerns about stability and soundness and unifying acceleration techniques across diffusion- and flow-based generators. A project page is available at https://yigu1008.github.io/SiD-DiT.

After significantly weakening other Iranian-backed groups in the region, Israel's military has turned its attention to the Houthis, carrying out a series of punishing strikes on Yemeni ports and other infrastructure. Last month an Israeli attack in Sana killed senior members of the Houthi-led government -- including the prime minister, Ahmed al-Rahawi -- but appeared to leave the group's military leadership largely unscathed. Israeli strikes in Yemen have also killed and wounded dozens of civilians in recent months, according to human rights groups. The United States has also bombed Yemen, in response to Houthi attacks on Red Sea shipping. The Houthis say they have targeted ships linked to Israel, although some of the ships they struck have no clear connection to the country. Houthi attacks on Israel are typically blocked or intercepted by the Israeli military, as was the case late on Thursday when sirens sounded in parts of Israel and the military soon after said that a missile from Yemen had been thwarted.

Here's a question that's been percolating since ChatGPT abruptly entered the mainstream: Does AI provide more avenues to enhance and augment education, or drive it into obsolescence? According to Under 30 Europe lister Joel Hellermark, the future of artificial intelligence and machine learning is rife with possibilities that can help the ways in which humans learn and collaborate, not replace them. He offered the calculator as a comparison: "If we think about it just like an insanely powerful calculator, you'd want everyone to just learn to use the calculator. Why should you sit there and do a bunch of calculations? The 26-year-old cofounder of software company Sana Labs has been immersed in the coding space since taking online Stanford courses at just 13 years old in Sweden. Now, at his startup, he's built an AI-driven software to help businesses manage workforce onboarding and training. The program pulls from correspondences, documents and the internet to answer questions and help train employees. Sana introduced the product to the world just as it was shutting down in 2020, and initially offered their platform to hospitals free of charge (over 2,000 took them up on the offer). Sana has since landed paying clients, including Klarna, Merck and Electrolux, and has raised $54.5 million. Hellermark, who dropped out of school at 19 to start the company, envisions a near future where the content we interact with is presented to us dynamically and with our personal contexts in play. "We're so used to creating content and then someone consumes the exact thing that you created– that goes all the way back to the printing press," says Hellermark. "It hasn't changed that much since.

Artificial intelligence is touching every aspect of how we engage with information (and much more) these days. Today, a startup building out a business based on one particular application of that -- how to apply AI to knowledge management in the workplace -- is announcing some funding as it finds some decent traction for its approach. Sana Labs -- which provides an AI-based platform to help people manage information at work, and subsequently to use that data as a resource for e-learning within the organization -- has closed a round of $34 million after seeing ARR grow seven-fold in the last year. Menlo Ventures, the U.S. VC firm, is leading the round for Stockholm-based Sana, with EQT Ventures and a whopping 25 angels and founder/operator individuals also participating. This is a Series B that values Sana at $180 million post-money.

In late June 2022, Sanas, a Silicon Valley startup, raised $32 million in Series A funding. Sanas is a real-time accent translation technology. For years, call centers in India or the Philippines have worked to neutralize accents by training their employees before they get to answering the phones. This new AI obviates that training – it alters accents in real time, making employees sound more American. From Sanas' perspective, they are working for the good of all concerned. The communication barriers between people with different accents and across multiple continents have lifted.

One of the reasons call center employees burn out so quickly is that they're frequently forced to deal with abusive callers. This abuse often comes in the form of bigoted tirades from American clients. Maxim Serebryakov, the 24 year-old CEO of Palo Alto-based accent augmentation company Sanas, saw this problem up close when his friend Raul Garcia Letona was forced to leave Stanford and support his family in Nicaragua by getting a job at a call center. Serebryakov began toying with the idea of using artificial intelligence to change a call center agent's accent in real time, and in 2020 co-founded Sanas. By processing a multitude of voices and corresponding transcripts through an algorithm, Sanas allows call center agents to choose how their accent will sound to clients.

"Now I have enabled the accent translation," he says. It's the same person, but he sounds completely different: loud and slightly nasal, impossible to distinguish from the accents of my friends in Brooklyn. Only after he had spoken a few more sentences did I notice a hint of the software changing his voice: it rendered the word "technology" with an unnatural cadence and stress on the wrong syllable. Still, it was hard not to be impressed – and disturbed. The man calling me was a product manager from Sanas, a Silicon Valley startup that's building real-time voice-altering technology that aims to help call center workers around the world sound like westerners.

A startup company based out of Silicon Valley called Sanas plans to use artificial intelligence (AI) to modify the voices of workers in call centers to remove their accents. The company's demo features the voice of a man with an Indian accent, reading through a call center script in a simulated customer interaction. Enabling the slider on screen to use Sanas' technology seamlessly switches from obviously human audio to a processed version that finds itself in the uncanny valley. The voice is still noticeably synthesized, but the Indian accent is gone and replaced with a more Americanized or "white" accent. Sanas launched in August 2021 and has already received large amounts of funding, with $32 million in funding secured during a Series A funding round in June 2022. The company's founders, three former students of Stanford University, claim the funding is the largest amount ever put towards a speech technology service.

"Now I have enabled the accent translation," he says. It's the same person, but he sounds completely different: loud and slightly nasal, impossible to distinguish from the accents of my friends in Brooklyn. Only after he had spoken a few more sentences did I notice a hint of the software changing his voice: it rendered the word "technology" with an unnatural cadence and stress on the wrong syllable. Still, it was hard not to be impressed – and disturbed. The man calling me was a product manager from Sanas, a Silicon Valley startup that's building real-time voice-altering technology that aims to help call center workers around the world sound like westerners.

Hosted by the Alan Turing Institute, AI UK is a two day conference that showcases artificial intelligence and data science research, development, and policy in the UK. This year, the event took place on 22 and 23 March, and participants were treated to a variety of interesting talks, panel discussions, and conversations on a wide variety of topics. The past year has seen much activity in the UK with regards to strategy, governance and policy. The policy-related sessions at AI UK provided the opportunity for participants to find out more about, amongst other things, the progress of AI-related legislation, regulation, the national AI strategy, the national AI Standards Hub, and how data is used at a governmental level. We take a look at three of the policy and strategy-related sessions that took place during the two days.