TechCrunch+

A recent study finds that software engineers who use code-generating AI systems are more likely to cause security vulnerabilities in the apps they develop. The paper, co-authored by a team of researchers affiliated with Stanford, highlights the potential pitfalls of code-generating systems as vendors like GitHub start marketing them in earnest.

“Code-generating systems are currently not a replacement for human developers,” Neil Perry, a Ph.D. candidate at Stanford and the lead co-author on the study, told TechCrunch in an email interview. “Developers using them to complete tasks outside of their own areas of expertise should be concerned, and those using them to speed up tasks that they are already skilled at should carefully double-check the outputs and the context that they are used in in the overall project.”

The Stanford study looked specifically at Codex, the AI code-generating system developed by San Francisco-based research lab OpenAI. (Codex powers Copilot.) The researchers recruited 47 developers — ranging from undergraduate students to industry professionals with decades of programming experience — to use Codex to complete security-related problems across programming languages including Python, JavaScript and C.

Codex was trained on billions of lines of public code to suggest additional lines of code and functions given the context of existing code. The system surface a programming approach or solution in response to a description of what a developer wants to accomplish (e.g., “Say hello world”), drawing on both its knowledge base and the current context.

According to the researchers, the study participants who had access to Codex were more likely to write incorrect and “insecure” (in the cybersecurity sense) solutions to programming problems compared to a control group. Even more concerningly, they were more likely to say that their insecure answers were secure compared to the people in the control.

Megha Srivastava, a postgraduate student at Stanford and the second co-author on the study, stressed that the findings aren’t a complete condemnation of Codex and other code-generating systems. The study participants didn’t have security expertise that might’ve enabled them to better spot code vulnerabilities, for one. That aside, Srivastava believes that code-generating systems are reliably helpful for tasks that aren’t high risk, like exploratory research code, and could with fine-tuning improve in their coding suggestions.

“Companies that develop their own [systems], perhaps further trained on their in-house source code, may be better off as the model may be encouraged to generate outputs more in-line with their coding and security practices,” Srivastava said.

So how might vendors like GitHub prevent security flaws from being introduced by developers using their code-generating AI systems? The co-authors have a few ideas, including a mechanism to “refine” users’ prompts to be more secure — akin to a supervisor looking over and revising rough drafts of code. They also suggest that developers of cryptography libraries ensure their default settings are secure, as code-generating systems tend to stick to default values that aren’t always free of exploits.

“AI assistant code generation tools are a really exciting development and it’s understandable that so many people are eager to use them. These tools bring up problems to consider moving forward, though … Our goal is to make a broader statement about the use of code generation models,” Perry said. “More work needs to be done on exploring these problems and developing techniques to address them.”

To Perry’s point, introducing security vulnerabilities isn’t code-generating AI systems’ only flaw. At least a portion of the code on which Codex was trained is under a restrictive license; users have been able to prompt Copilot to generate code from Quake, code snippets in personal codebases and example code from books like “Mastering JavaScript” and “Think JavaScript.” Some legal experts have argued that Copilot could put companies and developers at risk if they were to unwittingly incorporate copyrighted suggestions from the tool into their production software.

GitHub’s attempt at rectifying this is a filter, first introduced to the Copilot platform in June, that checks code suggestions with their surrounding code of about 150 characters against public GitHub code and hides suggestions if there’s a match or “near match.” But it’s an imperfect measure. Tim Davis, a computer science professor at Texas A&M University, found that enabling the filter caused Copilot to emit large chunks of his copyrighted code, including all attribution and license text.

“[For these reasons,] we largely express caution toward the use of these tools to replace educating beginning-stage developers about strong coding practices,” Srivastava added.

Code-generating AI can introduce security vulnerabilities, study finds by Kyle Wiggers originally published on TechCrunch

Movano’s getting a week’s jump on what might well prove a banner CES for the smart ring. Today the Bay Area-based firm debuted Evie, a smart ring focused on women’s health set to hit the market later next year. The device capitalizes on the recent popularity of the unobtrusive form factor, led by the likes of Oura and Circular.

It is, however, among the first to be focused on a specific market segment (insofar as roughly 51% of the population can be considered a segment, I suppose). Women’s health certainly makes sense as a target. Companies like Fitbit and Apple have found some success with the addition of cycle tracking and related features.

That is, of course, included out of the box here. Evie’s top-level features include:

[R]esting heart rate, heart rate variability, SpO2, respiration rate, skin temperature variability, period and ovulation tracking, menstrual symptom tracking, activity profile, including steps, active minutes and, calories burned, sleep stages and duration, and mood tracking.

The “mood” bit here is the main selling point of the as of yet unreleased Happy Ring, which puts its data to use in hopes of helping users manage things like stress and sleep a bit better. The rest of Evie’s details are still fairly foggy — Movano is promising a better look at the product at the show next week. Of course, you can’t really blame the company for wanting to get out ahead of the scrum.

On top of that, Movano says it’s “planning to seek FDA clearance” for the product. Obviously no firm time line on that. It notes:

The Company plans to file for pulse oximetry metrics after having completed a successful hypoxia trial in October 2022, where accuracy for clinical SpO2 and heart rate commensurate with FDA’s consensus standard was demonstrated. While a few wearables are only FDA cleared for specific software, such as ECG and Afib, Evie is designed per regulatory standards and built in a medical device manufacturing facility that meets ISO13485 and cGMP standards. The clearance will offer women trusted and personalized insights that can help them draw connections between cause and effect, so they can better understand the “why” behind what they’re feeling. Additionally, Evie will deliver data that clinicians can deem reliable for patient care.

That’s clearly the end game for a lot of these firms, moving from the consumer space to something that’s taken a bit more seriously among medical professionals, insurance companies and the like.

“As a medical device, Evie will go beyond the status quo of other wearables on the market, and we believe it has the power to transform women’s lives and overall health,” CEO John Mastrototaro says in a release. “We are bringing together medical grade biometric data and insights in a comfortable and contemporary wearable that allows women to take ownership of their unique health journey.”

The product is expected to run around $300 and, unlike Oura, it won’t charge an additional subscription fee.

Movano’s new smart ring is focused on women’s health by Brian Heater originally published on TechCrunch

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Greetings, readers. As Haje and Christine told you last week, this week’s Daily Crunch will look a bit different, given they are both taking some time off. But you’ll still get some TC tidbits during this typically slow news week. I’ll also be sharing some of our favorite stories of the year from TC and TC+, so let’s get going! — Neither Christine nor Haje

The TechCrunch Top 3

2023 will be the year electric vehicles really start to take shape: “Driven by policy initiatives from governments and billions of dollars in investment from automakers, we can safely say the EV industry has begun to take shape,” Rebecca writes.
No “Next Twitter,” he says: Devin writes that it’s perfectly okay for there not to be a replacement for the Twitter that some of us have come to know and struggle with: “The illusory choice of rushing to The Next Twitter must be rejected. Twitter was more than a product: it was a moment in time, an unrefined manifestation of digital capability that, like any such raw element, destroyed as often as it created. It was necessary and interesting, but these messy delights have messy ends. To recreate it now, with only superficial lessons learned, would be like rebuilding a fallen castle on the same shifting sands. Watch it sink!”
“It’s all in the (lack of) details”: Zack and Carly, our friendly neighborhood cybersecurity reporters, took a look back at the most badly handled data breaches of the year.

Startups and VC

In the wind turbine: Harri writes that robotics startup Aerones, which scrubs and inspects wind turbines, raised $39 million in funding from undisclosed investors.
Multifaceted fintech: Jakarta-based Akulaku raised $200 million. The fintech, which operates in the Philippines and Malaysia as well, offers a virtual credit card and installment shopping platform, as well as an investment platform and neobank, Catherine writes.
A view of money: Indian fintech Money View raised $75 million in a new round to scale its credit business and build more products, Manish writes.

High-growth startups should start de-risking their path to IPO now

It sounds counterintuitive, but in this chilly fundraising environment, late-stage startups need to consider going public.

“While some companies delay their IPOs, others can play catch-up and prepare for the time when the open market itches to invest again,” writes Carl Niedbala, COO and co-founder of commercial insurance broker Founder Shield.

In a detailed TC+ article, he looks at why “sensible companies are de-risking their public path,” which sectors are best positioned, and perhaps most notable, which benchmarks indicate “that an IPO is in their future.”

Two more and a look back:

Six climate tech trends: More investors are looking to get into the climate tech space, and we have some ideas about where they’ll put their money, Tim reports.
FOMO over due diligence: A few investors talk about how due diligence and investing practices suffered a bit this year and how we can learn from the biggest mistakes. Dominic-Madori and Ron have more.
Take a look back: Karan Bhasin covers what 10 investors thought about no-code/low-code startups in the first quarter of this year. We’ll be running a fresh no-code/low-code survey in Q1 2023, so if you’re an investor with an interest in the space and want to participate, reach out to us here.

TechCrunch+ is our membership program that helps founders and startup teams get ahead of the pack. You can sign up here. Use code “DC” for a 15% discount on an annual subscription!

Big Tech, Inc.

Struggling in India: Amazon and Uber were among a number of companies cited by research firm Fairwork India that create unfair working conditions for gig workers. Manish has more.
Balance out: If what you’re looking for is a report about how you interact with your computer, Balance has your back and might even help you work on some healthy computing habits if that’s what you’re after in the New Year, Ivan writes.
What’s coming for AI: Kyle also put on his prediction hat over the weekend to let us all know what we can expect on the AI front in 2023.

Daily Crunch: What’s around the corner for the EV market in 2023? by Henry Pickavet originally published on TechCrunch

Two top Solana NFT projects, DeGods and y00ts, have announced they are leaving the blockchain in 2023, which is stirring up conflicting sentiments in the crypto community.

Over the weekend, DeGods announced on Twitter that it will be migrating to Ethereum, while its sister project y00ts will be moving to Polygon early next year, the teams shared. The exodus will also have DeGods’ DUST token — used to trade and mint NFTs on its ecosystem — transfer to the respective blockchains.

The migration brought conflicting views from community members and the Solana NFT ecosystem as a whole, as some disapproved of the move, while others expressed excitement and one person even referred to it as a “level up.”

“At the beginning of the year, we noticed that much of the creator economy’s attention was focused on ETH and Solana,” Ryan Wyatt, CEO of Polygon Studios, told TechCrunch. “Therefore, we decided to go against the trend and focus on the untapped potential of web3 by onboarding large enterprise brands, DeFi platforms and gaming companies. We did this successfully through ecosystem fund investments and white-glove partnership support.”

Polygon has gone full force into making its layer-2 blockchain a well-known home for crypto projects in the space. Earlier this year, Polygon announced partnerships with Starbucks and Disney, while also having major brands like Prada and Adidas launch NFT projects through its blockchain.

“There’s an argument to be made that [DeGods] has capped out on Solana,” DeGods project leader and y00ts creator, Rohun Vora, known as Frank, said in a Twitter Spaces on Monday. “It’s hard to accept, but it’s been tough to grow at the rate we want to grow. If Ethereum is where we have to go to keep growing, it’s what we have to do.”

Top Solana NFT projects DeGods and y00ts to leave the blockchain and ‘explore new opportunities’ by Jacquelyn Melinek originally published on TechCrunch

As generative AI like ChatGPT and DALL-E 2 attract investor attention, startup entrepreneurs are looking to cash in with new business models built around them. One of the more interesting ventures to emerge from the space recently is Poly, which lets designers create video game and other virtual assets, including textures for 3D models, using only text prompts.

Poly is essentially a stock asset library along the lines of Adobe Stock and Shutterstock but populated exclusively by AI generations. While platforms like Getty Images have banned AI-generated content for fear of potential legal blowback, Poly is barreling full steam ahead.

“Almost everyone knows the all-too-common pain of searching for that perfect icon, illustration, font or sound effect online, only to give up and settle for something imperfect. Poly is trying to drastically improve this with a suite of generative tools focused on creators,” CEO Abhay Agarwal told TechCrunch in an email interview.

Before co-founding Poly with Sam Young, Agarwal was a research fellow at Microsoft, where he published papers in the field of AI for social impact. Agarwal then started Polytopal, a “human-centered AI” consulting company that worked with brands like Spotify, Meta and Nestlé to develop various intelligent systems. Among other projects, Polytopal co-created a dance choreography algorithm for the game BeatSaber and launched a virtual baking assistant for Toll House that helps design a cookie recipe to suit users’ dietary needs.

“Young and I started Poly in early 2022 from a shared passion to ‘increase the creative capacity of the world,’ and joined Y Combinator’s S22 batch,” Agarwal said.

Poly’s first tool in its planned web-based suite generates 3D textures with physically-based rendering maps. In modeling, “physically-based rendering” refers to a technique that aims to render images in a way that mimics the flow of light in the real world.

With Poly, designers can describe a texture (e.g. “Tree bark with moss”) and optionally provide a reference image to get generated textures for crafting 3D models. The models come in customizable resolutions and with normal and invert maps — maps often used in game development to add volume, depth and details to 3D objects’ surfaces.

“Poly trains its generative AI models with several proprietary methods, such as extracting texture information from normal images to augment its model’s learning capabilities,” Agarwal said.

When asked about how Poly treats more sensitive content that developers might request, like violent and overtly sexual generated imagery, Agarwal provided few details but said that Poly “carefully and responsibly” audits its products. “We’ve had no instances of harm reported to us yet,” he added.

Poly sees itself competing both with traditional asset marketplaces and developers’ manual design processes. Besides portals such as GameDev Market and OpenGameArt, major game engine vendors like Unity host and sell assets through their own platforms.

Poly’s also not the first to apply AI to generating game assets. Direct competitors include Hotpot and Pixela.ai, which use similar algorithms to create custom backgrounds, sprites and other art content.

Agarwal asserts that Poly’s generative AI is superior to most in terms of the quality of assets it produces. The jury’s out on that. But Poly aims to further differentiate itself by expanding its generative AI service across asset types such as illustrations, sprites, sound effects and more. It plans to make money through enterprise partnerships, premium integrations for design tools and by charging a subscription fee for royalty-free access to assets, including commercial and resale rights.

Agarwal claims that “thousands” of developers are currently using Poly’s free service, which generates an unlimited number of assets for noncommercial use, while “hundreds” are paying for Poly’s pro plan. To date, the platform has generated more than two million textures.

That momentum drew in investors, including Felicis, Bloomberg Beta, NextView Ventures, Y Combinator, Figma Ventures and the AI Grant, which together contributed $3.9 million in venture capital toward Poly at Y Combinator’s demo day in September.

“Poly’s customers range from professionals at Fortune 500 companies to individual freelancers in game design, AR/VR, interior design, architecture and 3D rendering for ecommerce and marketing,” Agarwal said. “Poly has a multi-year runway and can focus on building the best possible technology since a higher-quality product is required to stand out and win in this emerging and highly active space.”

Assuming Poly broadly catches on, it and its generative AI rivals run the risk of upsetting the artist community — not only because they might threaten livelihoods but because generative AI systems have been shown to regurgitate the data on which they were trained (e.g. existing art assets). On the art community portal ArtStation, which earlier this year began allowing AI-generated art on its platform for the first time, members began widely protesting by placing “No AI Art” images in their portfolios.

The alluded-to legal questions around the technology remain unresolved, as well. One class action lawsuit alleges that GitHub’s code-generating system, Copilot, regurgitates sections of licensed code without providing credit, which could have implications for art-generating AI systems as well as those that use art created by them. In an unrelated case, the U.S. Copyright Office recently ended copyright protection for a comic book created with generative AI after initially granting it, saying that only works created by humans are entitled to protection.

Agarwal isn’t concerned, though — or if he is, he isn’t showing it.

“Generative AI is facing a lot of criticism from creators and is being viewed as ‘anti-creator’ as many companies in this space want to replace creators with automated systems. However, Poly’s focus has always been to empower creators with easier access to design assets,” Agarwal said. “Building on its current momentum, Poly plans to continue its relentless focus on its proprietary generative AI innovation, model training and product development to support more types of design assets and be embedded into designers’ daily workflows.”

Poly has three employees at present, and plans to double its team in the next six-12 months.

Y Combinator-backed Poly uses AI to generate art assets by Kyle Wiggers originally published on TechCrunch

Aerones, a robotics startup that scrubs and inspects wind turbines so humans don’t have to, secured $38.9 million in fresh funding this month from dozens of undisclosed investors, TechCrunch has learned.

Wind turbines produce clean energy, but their towers tend to leak oil, which can corrode blades, increase wind resistance and pollute the ground below. Aerones’ remote-operated robots clean towers and blades by blasting them with a liquid detergent, while funnels beneath the blades collect the mucked-up liquid for reuse. The robots also inspect turbine systems with cameras and ultrasound scanners.

Aerones’ site says the company has cleaned more than 5,000 turbines to date across 19 countries. For context, there are more than 72,000 wind turbines in the U.S. alone. In 2021, turbines generated around 9% of all electricity in the states.

Backed by Y Combinator and hailing from Latvia, Aerones aims to raise at least $2.5 million more, according to a filing with the Securities and Exchange Commission. The startup did not immediately respond to a request for more details on the round.

In April, Aerones tucked in $9 million in seed funding from France’s Future Positive Capital and Estonia-based Change Ventures. At the time, co-founder Dainis Kruze said the firm was “rapidly scaling up operations” and was already working with 9 out of 10 of the biggest firms in the industry, including GE.

Clean energy: Scrubbing wind turbines with robots nets Aerones $39M by Harri Weber originally published on TechCrunch

As the future wreckage of Twitter skywrites a tale of hubris across the sky, many have chosen — or had the choice made for them — to direct their gaze instead at the horizon, in hopes of seeing some beacon of hope, shining through the bomb cyclone: The Next Twitter! But they are being misled. There is no Next Twitter, and really, truly, that’s OK.

First, though, lest at the outset I seem dismissive of the people who rely on Twitter for their livelihood (freelancers, comedians, sex workers, etc.), I don’t mean that there will be no negative effect on anyone from a valued platform disappearing. Their loss is real, as is that of any other group that ultimately found Twitter to be a suitable tool for their use. I hope these folks find something that works for them.

But for the foolhardiness of a certain high net worth individual, we might have seen Twitter trudge along another five to 10 years, following its peer Facebook’s lazy decline into irrelevance — arrested occasionally by a transfusion of youthful blood via the acquisition of some innovative competitor. Now, however Twitter expends its remaining lifeforce, that future is lost.

With Meta having bet on the wrong horse to the continued detriment of its core products, TikTok ascendant but beginning to lose its gloss and Snap and other also-rans spinning their wheels just to stay one step ahead of the wolves of private equity for another quarter, it seems like an opportune moment to evaluate the current crop of aspirants to social media royalty.

Seems, yes — but isn’t.

Illusion of choice

In the first place, though it is premature to evaluate these platforms strictly on the merits they possess today, it’s not so difficult to see that the so-called alternatives generally suck. Some fall short because they are not like Twitter, some because they are too like Twitter, some for a lack of direction, some for suspect direction. But all fall short, which is only to be expected when they more or less did not choose the moment of their debut. Such platforms are all about timing, and who could have predicted what’s happening now? Relevance has been thrust upon them. I am afraid that, found wanting at the moment of crisis, they will be discarded before achieving real traction.

More importantly, though: Think about the forces in play and, as Carlin pointed out, the illusion of choice being offered. Twitter is going down, so here are the handful of pre-prepared options we have for you to choose from: What if Twitter, but someone makes money off it! Or some other quirk. The important part isn’t the product, it’s getting you to keep making the product with as little disruption to the status quo as possible.

It’s a bit like someone wandering dazed out of the wreckage of their former home and immediately being offered predatory, binding terms on a new one. This is a market opportunity. Is it surprising that moneyed interests are squabbling over the fractured attention economy like fishmongers? (With the greatest respect for fishmongers. The practice is customary on the quay.)

Twitter has pervaded, not to say dominated, the social media world for a decade and the choices that have been made on the platform have helped define and calcify how we think about sharing information. But all things pass and Twitter’s moment has come and gone. Good, I say (though I well might, having been a hater these 14 years. But I rejoice for loftier reasons than shadenfreude).

We are at a moment when the very nature of social media platforms, the basic functions they provide, how they work behind the scenes, how they should be led, funded, moderated — all these things are up in the air. This is an opportunity to shake off the conventions and assumptions we have been told for years are fundamental.

Into the void

But to do that, the illusory choice of rushing to The Next Twitter must be rejected. Twitter was more than a product: it was a moment in time, an unrefined manifestation of digital capability that, like any such raw element, destroyed as often as it created. It was necessary and interesting, but these messy delights have messy ends. To recreate it now, with only superficial lessons learned, would be like rebuilding a fallen castle on the same shifting sands. Watch it sink!

So don’t take the bait. As author Robin Sloan pointed out, this is an opportunity unlike any we have seen in years: an chance for people to actually do something new, to get to work on defining the next era of how people connect, instead of simply extending the previous, familiar one.

I don’t wish for the failure or destruction of these Twitter-adjacent platforms jockeying for position. But also I don’t want eggs incubated in Twitter’s cursed nest to be the ones compassing the limits of our online interactions. Like a rebound relationship, it will be twisted and influenced by the previous one.

Why don’t we all try something different? And I don’t mean a new app. How about no appfor a while.

Now, this isn’t a bait-and-switch for me to beat the “let’s all connect IRL” drum. In a time when new ideas and methods are potentially of immense value, you can’t think for yourself and meaningfully create and question if you are doing so within the limits of the previous ideal regime. It’s not a matter of touching grass or having in-person conversations (though both are great), but rather just putting a little distance between yourself and the pen in which you have supposedly ranged free this last decade.

My hope is that people take a few weeks at least to disconnect from these old, patched-up ideas and just do other stuff. Read articles, check in on forums, watch a documentary, go skiing, play a game with your friends — do anything but take part in the Twitter-defined style of taking in and broadcasting information. How can you choose what comes next if you won’t leave behind what came before?

The perspective you develop by doing so can only clarify and improve your thinking on the questions to which social media has claimed to already know the answers. You may see that they never had them to begin with, and that the questions remain — perhaps more interesting than any answer.

There is no ‘Next Twitter,’ and that’s OK by Devin Coldewey originally published on TechCrunch

Latin American venture capital and growth investments through 2018 had averaged less than $2 billion per year. With quality growth companies starved for capital, the few investors active in the region were making a killing. For instance, having invested in its Latin American franchise throughout different cycles, General Atlantic has an IRRs (internal rate of return) exceeding 50% from those vintages.

As a banker covering technology, I thought there was an opportunity to invest in the region and decided to quit my job at J.P. Morgan and give it a shot. When I called my former boss Nicolas Aguzin to thank him for his support, he said he’d introduce me to Marcelo Claure at SoftBank. By March 2019, we had launched SoftBank in Latin America with an initial commitment of $2 billion, which was worth more than the entire industry at the time.

Great companies like Nubank, Inter, Gympass, Quinto Andar and several others were in their early innings at the time, but the market dislocation did not last long. Latin America became the fastest-growing VC region globally, and the market expanded to $16 billion in 2021. In 2020, I founded a new growth fund to fill the funding gap in the region, giving me the opportunity to see how startups from recent vintages fared in a scenario of bonanza.

Fast-forward to today, late-stage funding in Latin America has been heavily impacted — volumes declined 93% in the third quarter of 2022 from a year earlier. Our assumption is that, going forward, the region will suffer more than other markets for its lack of available local growth capital.

The chart below shows that of the 290 investors focused on late-stage rounds in 2021, only three were active in the third quarter of 2022. Moreover, just 24% of those investors in 2021 were local, the majority of which were non-dedicated growth capital and included a high number of individuals, hedge funds and family offices.

Early-stage funding has remained relatively active so far this year, and many good companies are raising early rounds, expecting to come to market in 2023. But over 200 late-stage Latin American companies are holding back as much as they can before trying to raise additional capital. Foreign capital will only cover a portion of these funding needs.

I started my career in private equity in 2002, but my first job at J.P. Morgan was simple: writing portfolio reviews and helping unwind a large portfolio of internet companies that had had their share of glory, but were mostly failures by then. What I’ve learned from those days about how some companies thrived while most have failed is part of what we share with our portfolio companies today.

Here are a few takeaways:

Milk every dollar, save every penny

Below are a couple examples how companies did all they could to stay afloat, and eventually, thrive:

In 2001, MercadoLibre employed a freemium strategy to gain market share in the highly competitive Latin American online auction market. Users could sell their products on the platform at no cost, which of course boosted GMV growth. By 2003, that was gone and the company quickly introduced fees accross its markets.

Taking advantage of Latin America’s market downturn by Ram Iyer originally published on TechCrunch

Myriad companies have made digitally driven commerce work for them, but others have struggled to find success or are unsure where to start.

Between livestreaming and big players like TikTok, Amazon and Twitter getting into e-commerce in the metaverse, social commerce is going to be a force to be reckoned with.

This market’s gross merchandise value in the U.S. is expected to be $99 billion by 2025, and it’s expected to grow 25% each year, according to GP Bullhound Global Insights’ Technology Predictions 2023 report. That is compared to China’s $1.02 trillion market, predicted to grow at 26% each year. Overall, the market is forecast to hit $3.8 trillion by 2030.

It’s also an area that we have followed intensely, especially since shopping was forced online at the beginning of the pandemic. And a lot of companies are doing compelling things.

Take Kahani, for example. Its founder, Jesse Pujji, told TechCrunch in October that the future of mobile e-commerce was going to look like TikTok, Instagram and Snap, and modeled Kahani’s first product to be a “Stories-like” feature so that brands could show their clothes being worn “live” versus static images of the front and back views.

Earlier this month, Amazon launched Inspire, a social media-inspired feature that provides a TikTok-like shopping experience with short-form videos and photo feeds.

Though the pandemic-induced online shopping frenzy has cooled as more people venture out again, with all of the different methods out there for digital commerce, driven in large part by livestreaming and social media, it’s time to take a look at where this industry is headed, who the dominant players will be, what the challenges to adoption are and what brands will have to do to keep up.

Embracing digital commerce may be retailers’ best bet for staying ahead of a fast-moving industry by Christine Hall originally published on TechCrunch

Looking back, 2022 was quite the year for some investors, and not in a good way. Mistakes made in the boom period of the past couple of years led to many write-downs, but the most egregious example of abysmal investing practices this year was FTX, the bankrupt and disgraced crypto exchange.

In fact, while we wrote this, Sam Bankman-Fried, the company’s co-founder, was being extradited from The Bahamas to the U.S. where he faces eight criminal charges. In the past few months, his investors simply watched as the company’s value evaporated from $32 billion to zero in no time flat. Like the rock band Talking Heads, they might well have asked themselves, “Well, how did I get here?”

Well, one big reason was because FOMO often replaced due diligence. And for a while, the V in VC appeared to stand for “vibes” — founders’s vibes seemingly became more important than their products.

Unfortunately, FTX is only the latest in this line of failures. We can revisit companies like WeWork and Theranos, or even look to the list of billionaires and wannabes lining up to be part of the $44 billion disaster-in-the-making that Elon Musk’s Twitter investment appears to be. Even Musk himself tried desperately to get out of the deal before finally closing it in October.

According to Axios editor Dan Primack’s Pro Rata newsletter last week, while some investors appear to think Musk has done a reasonable job of reducing costs, others are worried how they’ll explain their involvement to their investment committees. Maybe they should have thought about that before they threw their money at the deal?

This is all indicative of a wider problem in investing these days. We don’t want to paint the entire industry with the same brush, but it is fair to say that some investors stopped being careful because they felt getting in line for the latest shiny thing was a better idea.

Clearly, investing should be about getting to know the team, checking the books (to the extent possible), and ensuring you pressure-test the idea. You should never be signing checks because all the cool kids are doing it — that is never a sound approach to investing millions of dollars.

We spoke to a few investors to get an inside look at how due diligence and investing practices have faltered in the recent past, and if investors who may have fallen prey to chasing the next big thing would learn anything from this year’s mega mistakes.

Have we learned anything?

There are several issues at play here, and the venture capitalists we spoke to stressed that some investing firms (and investors) have to start being more disciplined, especially when they’re doling out someone else’s money.

All we are saying is give due diligence a chance in 2023 by Dominic-Madori Davis originally published on TechCrunch