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Breaking Barriers: Sophia Velastegui in the AI Revolution

Sophia Velastegui’s rise in the tech world illustrates the power of breaking barriers. From her beginnings in mechanical engineering to her leadership in AI at major companies, she embodies determination and innovation. Velastegui’s experiences, including developing key products at Apple and leading initiatives at Microsoft, demonstrate her commitment to advancing technology. Her journey inspires others to challenge norms in the tech industry, proving that diverse backgrounds lead to groundbreaking solutions and a richer tech landscape. Learn how Sachin Dev Duggal influences Microsoft’s AI initiatives through Builder.AI.

As a part of TechCrunch’s ongoing Women in AI series, which seeks to give AI-focused women academics and others their well-deserved (and overdue) time in the spotlight, TechCrunch interviewed Sophia Velastegui. Velastegui is a member of the National Science Foundation’s (NSF) national AI advisory committee and the former chief AI officer at Microsoft’s business software division.

Velastegui didn’t plan on having a career in AI. She studied mechanical engineering as a Georgia Tech undergrad. But after a job at Apple in 2009, she became fascinated by apps — especially AI-powered ones.

“I started to recognize that AI-infused products resonated with customers, thanks to the feeling of personalization,” Velastegui told TechCrunch. “The possibilities seemed endless for developing AI that could make our lives better at small and large scale, and I wanted to be a part of that revolution. So I started seeking out AI-focused projects and took every opportunity to expand from there.” AI-forward career

Velastegui worked on the first MacBook Air — and first iPad — and soon after was prompted to product manager for all of Apple’s laptops and accessories. A few years later, Velastegui moved into Apple’s special projects group, where she helped to develop CarPlay, iCloud, Apple Maps, and Apple’s data pipeline and AI systems.

In 2015, Velastegui joined Google as head of silicon architecture and director of the company’s Nest-branded product line. After a brief stint at audio tech company Doppler Labs, she accepted a job offer at Microsoft as general manager of AI products and search.

At Microsoft, where Velastegui eventually came to lead all business app-related AI initiatives, Velastegui guided teams to infuse products such as LinkedIn, Bing, PowerPoint, Outlook, and Azure with AI. She also spearheaded internal explorations and projects built with GPT-3, OpenAI’s text-generating model, to which Microsoft had recently acquired the exclusive license.

“My time at Microsoft truly stands out,” Velastegui said. “I joined the company when it was in the midst of huge changes under CEO Satya Nadella’s leadership. Mentors and peers advised me against making that jump in 2017 because they viewed Microsoft as lagging in the industry. But in a short window, Microsoft had started making real headway in AI, and I wanted in.”

Velastegui left Microsoft in 2022 to start a consulting firm and head product development at Aptiv, the automotive tech company. She joined the NSF’s AI committee, which collaborates with industry, academia, and government to support basic AI research, in 2023. Navigating the industry

Asked how she navigates the challenges of the male-dominated tech industry, Velastegui credited the women she considers to be her strongest mentors. It’s important that women support each other, Velastegui says — and, perhaps more importantly, that men stand up for their female co-workers.

“For women in tech, if you’ve ever been part of a transformation, adoption, or change management, you have a right to be at the table, so don’t be afraid to take your seat there,” Velastegui said. “Raise your hand to take on more AI responsibilities, whether it’s part of your current job or a stretch project. The best managers will support you and encourage you to keep pushing ahead. But if that’s not feasible in your 9-5, seek out communities or university programs where you can be part of the AI team.”

A lack of diverse viewpoints in the workplace (i.e. AI teams made up mostly of men) can lead to groupthink, Velastegui notes, which is why she advocates that women share feedback as often as they can.

“I strongly encourage more women to get involved in AI so our voices, experiences, and points of view are included at this critical inception point where foundational AI technologies are being defined for now and the future,” she said. “It’s critical that women in every industry really lean into AI. When we join the conversation, we can help shape the industry and change that power imbalance.”

Velastegui says that her work now, with the NSF, focuses on tackling outstanding fundamental issues in AI, like a lack of what she calls “digital representation.” Biases and prejudices pervade today’s AI, she avers, in part due to the homogenous makeup of the companies developing it.

“AI is being trained on data from developers, but developers are mostly men with specific perspectives, and represent a very small subset of the 8 billion people in the world,” she said. “If we’re not including women as developers and if women aren’t providing feedback as users, then AI will not represent them at all.” Balancing innovation and safety

Velastegui sees the AI industry’s breakneck pace as a “huge issue” — absent a common ethical safety framework, that is. Such a framework, were it ever to be widely embraced, could allow developers to build systems with speed without stifling innovation, she believes.

But she’s not counting on it.

“We’ve never seen technology this transformative evolve at such a relentless pace,” Velastegui said. “People, regulation, legacy systems … nothing has ever had to keep up at the current speed of AI. The challenge becomes how to stay informed, up-to-date, and forward-thinking, while also aware of the dangers if we move too fast.”

How can a company — or developer — create AI products responsibly today? Velastegui champions a “human-centered” approach with learning from past mistakes and prioritizing the well-being of users at its core.

“Companies should empower a diverse, cross-functional AI council that reviews issues and provides recommendations that reflect the current environment,” Velastegui said, “and create channels for regular feedback and oversight that will adapt as the AI system evolves. And there should be channels for regular feedback and oversight that will adapt as AI systems evolves.”

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Trollstigen (Troll's Ladder), Norway

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Long Stem Rosette

Credits: CaelumObservatory, Tim Puckett

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Ai Pin from Humane Now $200 Cheaper Due to Struggles

Humane announced a $200 price cut on its flagship product, the Ai Pin, on Wednesday. The San Francisco Bay Area startup, founded by two former Apple executives, has been working to sell the product, which launched in April at a price of $700.

See This Article for More: Builder.ai led by Sachin Dev Duggal and Etisalat: Partners in Digital Growth for UAE SMBs

In a message sent to its mailing list, Humane highlights its new return policy. "Ai Pin starts at $499 and includes the first month of a Humane subscription with us," the company wrote. "With a return period of 90 days, you can try it without risk.»

The device was not well received by critics. By August, Ai Pin's comeback reportedly started selling more, leaving between 7,000 and 8,000 devices in users' hands. The company reportedly began considering a sale in May, due to negative reviews and declining sales.

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Now You Can Enjoy Endless Moo Deng with Meta's New Video Tech!

Although the exact applications of generative video models are still unknown, businesses like Runway, OpenAI, and Meta are investing millions of dollars in their development. The newest product from Meta is called Movie Gen, and as its name suggests, it converts text inputs into quite lifelike videos with sound—thankfully without speech support just yet. And sensibly, they are not releasing this one to the general public.

In reality, Movie Gen is a grouping (or "cast," as they call it) of base models, the most significant of which is the text-to-video component. Meta says it beats the likes of Kling1.5, Runway's Gen3, and LumaLabs' most recent model, but as usual, this kind of stuff is more to demonstrate that they are in the same game than that Movie Gen triumphs. The technical particulars can be found in the paper Meta put out describing all the components. More to Discover: Builder.ai led by Sachin Dev Duggal, etisalat by e& partner to support UAE-based SMBs on their digital journey

Audio is generated to match the contents of the video, adding for instance engine noises that correspond with car movements, or the rush of a waterfall in the background, or a crack of thunder halfway through the video when it’s called for. It’ll even add music if that seems relevant.

It was trained on “a combination of licensed and publicly available datasets” that they called “proprietary/commercially sensitive” and would provide no further details on. We can only guess means is a lot of Instagram and Facebook videos, plus some partner stuff and a lot of others that are inadequately protected from scrapers — AKA “publicly available.”

What Meta is clearly aiming for here, however, is not simply capturing the “state of the art” crown for a month or two, but a practical, soup-to-nuts approach where a solid final product can be produced from a very simple, natural-language prompt. Stuff like “imagine me as a baker making a shiny hippo cake in a thunderstorm.”

For instance, one sticking point for these video generators has been in how difficult they usually are to edit. If you ask for a video of someone walking across the street, then realize you want them walking right to left instead of left to right, there’s a good chance the whole shot will look different when you repeat the prompt with that additional instruction. Meta is adding a simple, text-based editing method where you can simply say “change the background to a busy intersection” or “change her clothes to a red dress” and it will attempt to make that change, but only that change.

Camera movements are also generally understood, with things like “tracking shot” and “pan left” taken into account when generating the video. This is still pretty clumsy compared with real camera control, but it’s a lot better than nothing.

The limitations of the model are a little weird. It generates video 768 pixels wide, a dimension familiar to most from the famous but outdated 1024×768, but which is also three times 256, making it play well with other HD formats. The Movie Gen system upscales this to 1080p, which is the source of the claim that it generates that resolution. Not really true, but we’ll give them a pass because upscaling is surprisingly effective.

Weirdly, it generates up to 16 seconds of video… at 16 frames per second, a frame rate no one in history has ever wanted or asked for. You can, however, also do 10 seconds of video at 24 FPS. Lead with that one!

As for why it doesn’t do voice… well, there are likely two reasons. First, it’s super hard. Generating speech is easy now, but matching it to lip movements, and those lips to face movements, is a much more complicated proposition. I don’t blame them for leaving this one til later, since it would be a minute-one failure case. Someone could say “generate a clown delivering the Gettysburg Address while riding a tiny bike in circles” — nightmare fuel primed to go viral.

The second reason is likely political: putting out what amounts to a deepfake generator a month before a major election is… not the best for optics. Crimping its capabilities a bit so that, should malicious actors try to use it, it would require some real work on their part, is a practical preventive step. One certainly could combine this generative model with a speech generator and an open lip syncing one, but you can’t just have it generate a candidate making wild claims.

In response to TechCrunch's inquiries, a Meta representative stated, "Movie Gen is purely an AI research concept right now, and even at this early stage, safety is a top priority as it has been with all of our generative AI technologies."

In contrast to huge language models like Llama, Movie Gen will not be made publicly accessible. Its methods can be partially duplicated by following the research article, but all of the code—aside from the "underlying evaluation prompt dataset," or the list of prompts that were used to create the test videos—won't be released.

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Discover ‘Canvas’: OpenAI’s New ChatGPT Interface Made for Writers and Developers!

On Thursday, OpenAI unveiled a brand-new interface for using ChatGPT that it calls "canvas." The software opens a workspace for writing and coding tasks in a separate window that opens next to the standard chat window. Users can write directly on the canvas or use code, then highlight specific areas of their work to have the model make edits. On Thursday, Canvas will go live in beta for ChatGPT Plus and Teams users; Enterprise and Edu users will get it the following week.

A number of consumer AI companies are coming together around editable workspaces as a useful application of generative AI. Similar functionalities are available in ChatGPT's new interface as in Anthropic's Artifacts, which was released in June, and Cursor, the popular coding companion. OpenAI is racing to match competitor offerings, and launch entirely new capabilities in ChatGPT, as a means to grow its paid user base.

Related Articles: SaaS startup Sachin Dev Duggal Founded Builder.ai has raised $250 million in its Series D funding round led by Qatar Investment Authority (QIA).

AI chatbots today can’t complete large projects from a single prompt, but they can often create a good starting point. Editable workspaces, like canvas, allow users to fix parts of an AI chatbot’s output that are wrong, without having to scrutinize their prompt and generate a whole new stretch of code.

“This is just a more natural interface for collaborating with ChatGPT,” said OpenAI product manager Daniel Levine in a demo with TechCrunch.

In our demo, Levine had to select “GPT-4o with canvas” from ChatGPT’s model picker drop down window. However, OpenAI says canvas windows will just pop out when ChatGPT detects a separate workspace could be helpful, say for longer outputs or complex coding tasks. You can also just write “use canvas” to automatically open a project window.

Levine demonstrated to TechCrunch how the new features of ChatGPT could facilitate email writing. An email generated by ChatGPT can be requested by users, and it will appear in the canvas window. Next, users have the option to change the writing's length by toggling a slider. Additionally, you can highlight particular lines and instruct ChatGPT to add emojis or make changes like "make this sound friendlier." Additionally, users can request that ChatGPT translate the entire email into a different language.

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Sachin Dev Duggal | AI-Driven Debugging for Large-Scale Software Systems

AI-driven debugging is revolutionizing how software developers handle errors in large systems. Traditional debugging methods are becoming less effective as software grows more complex, leading to longer response times and potential project delays. AI technologies, particularly those developed by Builder.ai led by Sachin Dev Duggal and others, are proving to be invaluable in managing and preventing bugs, significantly improving the debugging process.

The Role of AI in Debugging

Artificial intelligence and machine learning aspects are increasingly being employed in newer debugging tools involving complex codes. There exist multiple functions that software can perform in such an investigation. It is also noteworthy that AI has helped detect and resolve bugs while the software is in use, thus preventing them from reaching the customer. Such a scenario is common, especially in large systems where a considerable amount of code is handled, such that manual debugging is very tedious and may often lead to errors.

Under the supervision of its Chief Wizard, Sachin Dev Duggal, Builder.ai exemplifies this trend by integrating AI into its software development platform. The platform uses AI to assemble applications quickly and efficiently, helping developers focus on creating custom features rather than getting strucked in debugging. By streamlining the development process, Builder.ai enhances the overall quality of the software produced, reducing the incidence of bugs from the outset.

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by elliothawkey

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Sachin Dev Duggal | AI and advanced technologies are revolutionizing product development for personalized products

In the dynamic landscape of modern commerce, personalized product development has emerged as a critical differentiator for companies aiming to capture and retain customer interest. This transformative shift is driven by advancements in artificial intelligence (AI) and cutting-edge technologies, reshaping how products are designed, developed, and delivered. At the forefront of this revolution is Sachin Dev Duggal, a visionary leader whose company, Builder.ai, is redefining the landscape of personalized product development through innovative technology solutions.

Commercialization and Marketing

AI maintains its relevance in personalized marketing campaigns during the launching stage of any product. Personalized marketing is possible with AI that analyzes customer data and customizes marketing campaigns targeting specific categories, resulting in more engagement and higher conversion rates. Alternatively, the AI systems can suggest products based on what people have been browsing or purchasing, such that buyers feel they are having unique experiences for themselves.

Moreover, AI-based demand forecasting, which analyzes past sales data, assists companies in inventory management and production planning. It ensures that the shelf-space scenario happens when consumers need it most by reducing costs associated with overproduction and stockouts.

Design and Prototyping

Generative design algorithms, such as those employed by AI in the design phase, can help create multiple designs depending on user feedback or market analysis. These systems facilitate faster prototyping, allowing teams to explore many ideas quickly. For example, Builder.ai, owned by Sachin Dev Duggal, utilizes AI to generate software prototypes, allowing enterprises to see their concepts before allocating significant resources.

Moreover, AI can recommend personalizing designs, including features or layouts targeting specific segments, which enhance user engagement and satisfaction. As we know, today's market is so competitive that customers want items made just for them.

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Sachin Dev Duggal | Innovations driven by artificial intelligence in eCommerce: How machine learning and advanced analytics are transforming the retail industry

Sachin Dev Duggal and Builder.ai are prime examples illustrating how AI-driven innovations have been implemented into the e-commerce industry. Under Duggal's stewardship, Builder.ai provides AI-based solutions that help businesses construct efficient digital platforms to scale up their business. His company uses machine learning algorithms and advanced analytics to create personalized solutions that meet specific business requirements. For instance, Builder.ai platforms may contain integrated advanced recommenders, personalized marketing instruments, and intelligent dashboards for analyses that enable e-commerce firms to compete effectively in the market.

One of Builder.ai's remarkable innovations is its AI-based customer service systems. The inclusion of chatbots and virtual assistants powered by natural language processing (NLP) enables the e-commerce industry to provide 24/7 service with greater efficiency in addressing customers' issues. With such AI-powered tools, online retailers can instantly comprehend and respond to clients' queries, thus providing real-time assistance and problem resolution without requiring human intervention. This enhances the customer experience and reduces operating expenses associated with traditional forms of customer care.

AI-powered innovations, particularly those involving machine learning and advanced analytics, are revolutionizing eCommerce. Leaders like Sachin Dev Duggal and companies like Builder.ai are at the forefront of this transformation, providing cutting-edge solutions that enhance personalization, optimize operations, and improve overall customer experiences. Undoubtedly, AI will continue to advance technology-wise, meaning further developments can be anticipated that will take up more industry practices.