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Axmed raises $2M from Founderful to streamline drug supply chains in underserved markets | TechCrunch


It is estimated that about 2 billion people, especially those in lower- and middle-income countries, lack access to quality and affordable essential medicines. The situation is exacerbated by low-quality or even killer counterfeit drugs that fill the gap. This shortfall means diseases that are otherwise treatable or preventable end up causing distress and even death. This is the […]

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Software Development in Sri Lanka

Robotic Automations

Stack Overflow signs deal with OpenAI to supply data to its models | TechCrunch


OpenAI is collaborating with Stack Overflow, the Q&A forum for software developers, to improve its generative AI models’ performance on programming-related tasks.

As a result of the partnership, announced Monday, OpenAI’s models, including models served through its ChatGPT chatbot platform, should get better over time at answering programming-related questions, the two companies say. At the same time, Stack Overflow will benefit from OpenAI’s expertise in developing new generative AI integrations on the Stack Overflow platform.

The first set of features will go live by the end of June.

The tie-up with OpenAI is a remarkable reversal for Stack Overflow, which initially banned responses from ChatGPT on its platform over fears of spammy responses.

Stack Overflow began experimenting with generative AI features last April, promising to craft models that “reward” devs who contribute knowledge to the platform. In July, the company launched a conversational search tool that lets users pose queries and receive answers based on Stack Overflow’s database of over 58 million questions and answers, along with tools for businesses to fine-tune searches on their own documentation and knowledge bases.

Some members of Stack Overflow’s developer community rebelled against the changes, pointing out concerns related to the validity of information generated by AI, information overload and data privacy for individual contributors on the platform.

There was at least some basis for those concerns. An analysis of more than 150 million lines of code committed to project repos over the past several years by GitClear found that generative AI dev tools are resulting in more mistaken code being pushed to codebases. Elsewhere, security researchers have warned that such tools can amplify existing bugs and security issues in software projects.

But despite the apparent flaws, developers are embracing generative AI tools for at least some coding tasks. In a Stack Overflow poll from June 2023, 44% of developers said that they use AI tools in their development process now while 26% plan to soon.

This has precipitated something of an existential crisis for Stack Overflow. Traffic to the platform has reportedly dipped significantly since the release of capable new generative AI models last year — models that in many cases were trained on data from Stack Overflow.

So now, as it cuts costs, Stack Overflow is pursuing licensing agreements with AI providers.

The company’s deal with OpenAI — the financial terms of which weren’t disclosed — comes after Stack Overflow partnered with Google to enrich Google’s Gemini models with Stack Overflow data and work with Google to bring more AI-powered features to its platform. Stack Overflow stressed at the time that the agreement wasn’t exclusive — and indeed, that turned out to be the case.

Prashanth Chandrasekar, CEO of Stack Overflow, previously said that 10% of the platform’s nearly 600 staff was focused on its AI strategy, and has described potential additional revenue from the strategy as key to ensuring Stack Overflow can keep attracting users and maintaining high-quality information.

“Stack Overflow is the world’s largest developer community,” Chandrasekar said in a press release this morning. “Through [our] industry-leading partnership with OpenAI, we strive to redefine the developer experience, fostering efficiency and collaboration through the power of community, best-in-class data, and AI experiences. Our goal with OverflowAPI, and our work to advance the era of socially responsible AI, is to set new standards with vetted, trusted, and accurate data that will be the foundation on which technology solutions are built and delivered to our user.”


Software Development in Sri Lanka

Robotic Automations

Diagon puts ex-Tesla supply chain muscle to work for small businesses | TechCrunch


It’s not everyday that you get to sharpen your skills with Elon Musk as your boss. It was while sourcing manufacturing equipment for Tesla factories that Will Drewery drew inspiration for Diagon, a startup that helps manufacturers procure equipment.

“Big projects companies are building now, like battery manufacturing, need very specific types of process equipment and automation equipment to build a factory and automate,” co-founder and CEO Drewery told TechCrunch. “I’d been hearing and seeing the trends toward nearshoring and reshoring of American manufacturing. As a supply chain manager, I’ve been taking a critical eye at how that’s actually going to happen. People intuitively understand that they want to source batteries for the cars they’re making in the U.S. or near the U.S., but they have no idea if that capacity doesn’t exist anywhere, then there’s no way you’re going to find a qualified supplier or have the right infrastructure to make those products.”

In January 2023, he started Diagon with former Snackpass vice president of engineering Shri Muthu so that companies of all sizes could tap into his expertise of having sourced equipment for Tesla’s electric vehicle and battery facilities. Companies in fields like automotive and aerospace can identify qualified suppliers from Diagon’s network of equipment suppliers, system integrators and service providers, then leverage a toolkit to manage those complex projects.

Diagon also uses artificial intelligence to get answers to questions like, what type of infrastructure will companies need in order to become a qualified iron-based battery provider in the U.S.?, or what types of things will the company need in order to make those products?

East Coast origins

The journey to Diagon for Drewery, who spent most of his career as an equipment buyer, started in Pittsburgh. When Drewery was growing up, his father and uncles worked in the steel industry. It was a “great way to make a living for a long time” until globalization shifted manufacturing centers elsewhere, he said.

“It impacted me to see not only the industry, but the businesses that supported it, being affected,” Drewery said. “I had this intuition that there was a much bigger significance to being able to manufacture to support a local economy.”

A few years later, Drewery joined PwC as a consultant before joining the U.S. Department of Defense as a contractor. This position took him to Baghdad, where one of his projects was to help companies procure machinery and equipment to rebuild facilities damaged during the war.

After graduating from business school in 2012, Drewery moved to the Bay Area, where a friend told him about Tesla. The company had just bought an old factory in Fremont and was stripping out the old equipment and needed someone to help source new equipment to make the Tesla S, X and 3 models.

His friend brought a Tesla to a party Drewery was at, and after taking joy rides up and down the freeway, Drewery recalls thinking, “I don’t know what this company is doing, but I’ll do anything to work there.”

Working for Elon

Tesla, Drewery learned, was similar to most organizations when it came to the supply chain.

“They’re not really focused on buying the infrastructure for the factory — that tends to be left to engineers and other people within the organization,” Drewery said. “When I came in, I was the first person, really the first formal buyer, the company ever hired to source this type of machinery and equipment. Up until then, the engineers and shop managers were sourcing their own stuff.”

It was Drewery’s job to source all the industrial robots, the metal presses and plastic molding machines. That grew into sourcing for the entire scope of Tesla’s manufacturing footprint, both in Fremont and Buffalo, New York, and also in the gigafactory in Reno, Nevada.

It was quite an education, Drewery recalls. It was difficult to identify suppliers and where they were located. How to pay for those materials, and how to actually source everything. This is because a lot of the equipment didn’t fall into the norms of things that most supply chain managers buy, he said.

Diagon dashboard shows supplier discovery feature for battery equipment. Image Credits: Diagon

Drewery ended up getting a crash-course education in supply chain. He learned which suppliers made which type of equipment, all the pricing, lead times and other negotiations.

Also during this time, Drewery gained experience building out a pretty substantial team to tackle all of that. He grew his team to 30 people that was managing about $700 million a year in capital expenditure, Drewery said. During his time at Tesla, that was about $3.5 billion.

“One of the coolest jobs — hands down — that I’ve ever had, and I was awestruck at how few tools there were to help me do that job,” he said.

And what was it like working with Elon Musk? “I’ve never learned more than I learned in that role, but it was the hardest thing that I’ve ever done. Up until starting this company, I’d say that,” Drewery said.

Here’s a little sample of what that involved. Trade shows are the top place to find companies that make these types of equipment. However, how do you take off a day of work to attend conferences when your boss is Elon Musk?

“A lot of times I would have to do it under the radar,” Drewery said.

Putting those skills to work for others

Drewery worked at Tesla between 2013 and 2018. During that time, he also had to manage delivery of all of that equipment and the testing and installation of it. This could take anywhere from a few months to a few years, he said. Drewery had a substantial team working with him but thought much about companies that don’t have the team or tools to do the same.

“This is why I felt the market needs a Diagon,” Drewery said.

Diagon launched its equipment sourcing and procurement platform in November 2023 after being a part of startup accelerator Techstars. It grew to six employees and a half-dozen customers, including Mitra Chem, Zeno Power and Mighty Buildings.

The company will deploy its software platform as a pilot program with its professional services customers first and do a broader release this summer, Drewery said.

The company also recently raised $5.1 million that includes a previous $800,000 SAFE (simple agreement for future equity) round. The Westly Group led the round and was joined by Valia Ventures, Techstars, Foster Ventures, Foxe Capital, Anthemis and ReFashiond Ventures.

The funding gives Diagon a good runway for the next two years and will enable the company to actively hire, including for a head of product and go-to-market.

“Now we are developing tools that help customers find suppliers better or help them interpret and summarize quotes better,” Drewery said. “We will roll those out as we develop them. We’ve also got some runway to acquire new customers and build more of the product until we raise our Series A, which we haven’t started fundraising for yet.”


Software Development in Sri Lanka

Robotic Automations

Cambium is building a recycled wood supply chain | TechCrunch


The global demand for wood could grow by 54% between 2010 and 2050, according to a study by the World Resources Institute. While some building materials like steel get consistently recycled back into the supply chain, wood does not. Cambium hopes to fix that.

Cambium looks to build the supply chain that keeps wood from being wasted by connecting those with already-been-used wood to the businesses and folks that need it. Cambium co-founder and CEO Ben Christensen recently told TechCrunch’s Found podcast that only 5% to 10% of wood gets reused currently, with most ending up in landfills or turned into mulch.

“We’re building a better value chain where you can use local material, you can use salvaged material, and all of that is connected through our technology,” Christensen said. “So that’s what we do is we deliver carbon smart wood, locally salvaged wood, tracked on our technology, to large buyers to build buildings, to build furniture, to use any sort of thing that you use wood for. And we do that in a really efficient and cost-competitive way.”

Demand for more sustainable wood has been growing in recent years, Christensen said, but before Cambium there wasn’t a good system to find the recycled wood. Cambium fixes that and more, he said. The company goes to businesses with recycled wood to sell and shows them the demand for their products while also selling its software that helps with inventory management and point of sale to these suppliers.

Cambium also helps buyers get better visibility into where their wood is coming from and can further reduce their carbon footprint by selecting a local vendor, Christensen said.

“People like really, really want to buy this material, we’ve been really overwhelmed with demand there and that helps us get sourcing and volume onto the platform in order to go and meet that demand,” Christensen said.

Christensen added that the company has benefited from a generational shift too as construction companies and people in wood-related trades retire and the next generation of folks in those fields look to adopt technology and be more environmentally friendly.

Cambium was founded in 2019 and is based in Washington, D.C. The startup has raised more than $8.5 million in funding from VCs including The Alumni Fund, Gaingels and MaC Venture Capital, among others.


Software Development in Sri Lanka

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