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Betaworks goes all-in on augmentative AI in latest camp cohort: “We’re rabidly interested”



Betaworks is no stranger to investing in artificial intelligence and machine learning, but the latest cohort of their Camp “thematic accelerator” indicates a confidence in the field beyond the present fascination with chatbots. Founder and CEO John Borthwick described the firm as being “rabidly interested” in the field of AI as augmentation rather than just a product in itself.

They’re not the only ones, either: “This particular Camp had twice the applicants as last year,” Borthwick told me. “The fun part of these is that you put out an open call, and under that banner, that thesis, you get more diversity than you expect. We believe that over the next 2-3 years, we’re going to see an incredible amount of companies building and using AI models to augment human workflows and behaviors.”

It is perhaps ChatGPT’s most universally useful quality that (assuming you can tell when it’s putting you on) it can quickly and satisfactorily answer a question on nearly any topic, or give a reasonable answer to something like a coding problem. Few talk with AIs just for the pleasure of it (though there are those who do); if it can make your work easier, why not let it?

Borthwick noted that Betaworks has been investing in AI and ML since 2016, when it was far more rudimentary.

“We started by going systematically through the intersection of ML and a particular modality: machine learning and audio, synthetic media, all those different objects of data or media,” he said. “Over the last year or two we’ve been thinking about the role of AI as it relates to human workflows, and we firmly believe, and want to invest in and move the market towards augmentation.”

This is like thinking of AI as “a bicycle for the mind” rather than a purely generative or self-contained product. That’s visible in the selected companies, many of which are or use AI to speed up or improve existing processes rather than do something completely new. Each will receive $500,000 in funding, in addition to anything they’ve already raised.

“We’re looking across the AI stack; certain things in this Camp are almost apps, then there are things that are much more in the middleware category,” Borthwick continued. “The program is really about finding product-market fit and developing a product roadmap, it’s less about performative fundraising exercises. About half of the companies do their raise before or during the program.”

They brought in three co-investors this year: Greycroft, Differential, and Mozilla, all of which will make co-investments and make their resources and networks available to the startups. Betaworks still does all the actual accelerator stuff.

Here are the 12 companies in this year’s cohort, summarized from summaries they sent over; I asked each company the most obvious question I could think of (in italics) after hearing what they’re trying to do. In the interest of brevity I have also summarized their sometimes extensive answers. There’s more detail on each including founders and their backgrounds over at Betaworks.

  • Armilla Assurance: A service for assessing the quality and reliability of AI systems. The company then offers insurance against losses due to AI performing below its assessed level.What metrics are used to assess AI risk and fitness, and if they’re industry standard, why would the company not just assess them internally?Armilla uses both industry standards and proprietary testing methods to provide an objective measure of quality and a performance warranty, though they are no substitute for including these measures in the development process.
  • Bionic Health: Preventative healthcare using an AI-driven model trained on data (“real-world practices, protocols and workflows of doctors, practitioners and patients”) from their own clinic in North Carolina. Has also built a smarter electronic health record system that uses embeddings for improved search and insights. $3.5M already raised in a seed round.Why I would want to use an AI model based on decisions by doctors and health specialists, rather than asking a doctor or other accredited health specialist?The system is assistive to doctors, not a direct to consumer thing, and the improved EHR should reduce clerical work in this setting, allowing doctors and patients to focus on making well informed care decisions.
  • Deftly: An ML platform that aggregates and synthesizes customer feedback and other signals into more easily actionable product changes and features.How would an early stage startup come by “troves of dispersed product feedback” to aggregate and synthesize?Not directly answered, but what data there is in any feedback forms, meeting notes, and other channels is ingested and shared in a dashboard for easier interpretation by product teams.
  • Globe: Creates large language models for teams that need to “gather, exchange, and understand complex information,” like in large scale studies or product development. The LLM ingests all relevant documents and can be consulted at any level of detail, from overview to technical details or exact quotes from relevant documents.Given LLMs’ limitations, why would I trust one to provide multiple levels of detail of complex data or projects?Surfacing useful information, and specifically information that one may not have been aware of to begin with, is the goal – as opposed to distilling new information out of it. It seems to act more as a semantically enhanced search.
  • GroupLang: Working on software that allows LLMs to interact with groups of people instead of individuals, a task that involves redefining user preferences, privacy, and other interesting questions.What’s an example of a group having to interact collectively with an LLM?It’s more that collective use could be beneficial, they say, such as a shared complex task where a central system is tracking information important to all involved.
  • Open Souls: Aims to create conversational AI models that “autonomously think and behave like real people,” complete with feelings and personalities and internal complexity.This is quite a claim. But doesn’t it more or less amount to a fine tuned model with an artificial persona loaded via initial instructions?Fine tuning personas primarily produces a change in speech patterns but not how the model operates internally. Their approach is to augment LLMs with extra non-visible processes to simulate “rich inner monologues” that inform behavior.
  • Pangaea: Using AI and some custom backend tech to build games faster and take on time-consuming tasks, with first-party development of a rogue-lite battle royale (Project Rise) with procedurally-generated maps. Competitive multiplayer games require careful gameplay and map balance. How can that be achieved with this level of procedural generation?Some games are more about perfect balances than others, and in this case it’s more important to make sure it’s “fair” and that loss doesn’t result directly from bad proc gen. There will be hand-designed rooms, challenges, levels, and rules to make sure the experience is well tuned. Plus if you die you are reborn as a monster and keep some of your progress.
  • Plastic Labs: Aims to improve LLM viability by “securely managing the flow of intimate psychological data between users and models.” So you get customization across different agents without it having to learn and stash your various preferences and tendencies every time.What does this framework actually consist of, and how can it remain effective if the AI apps in question all use different foundation models or tuning processes?A “secure middleware relay.” Certain approaches work across LLMs because all the foundation models seem to share an ability to “construct and comprehend predictions about internal mental states.” What exactly this ability amounts to is not clear (though the team has their theories) but they claim it enables their portable personalization.
  • Shader: A social camera app that lets users create AR filters using a simple, no-code interface including voice and simple taps and swipes.What does the process of creation look like and how can the filter be shared to proprietary platforms like Instagram or Snapchat?You describe what you want with a traditional prompt like “cyberpunk elf face” and then it can be mapped onto your face live. The filter itself stays on Shader, you’ll have to export videos to other services. Several examples on their IG and Tiktok.
  • Unakin: Also aiming to reduce development time with AI code assistants. First is a UI programming agent that builds functioning game AIs with text or visual prompts, with more to come. Does the proposed agent exist, and what specifically is it capable of right now compared to other code-generating LLMs?They’re using it internally for improved code search, code generation (not yet benchmarked but expected to be competitive in UI creation in particular), and an image-to-code process whereby Figma and Adobe files can be turned directly to in-game UI.
  • Vera: Helps workplaces adopt AI by filtering what goes in and out of the models, according to rules set up by the company. It’s basically the kind of oversight IT gets for other business software, but for generative AI.So this records all inputs and outputs from AIs used by an enterprise and allows closer controls over what is asked or answered?Basically yes — it addresses security and privacy concerns by making the interactions observable and intercepting things like sensitive info before they get sent to the LLM. Responses can also be checked for consistency and errors.
  • Waverly: A “social network of ideas” that uses AI to “remix” them, and uses conversational AI as a control method for the feed. How exactly does the AI model ‘remix’ ideas, and how does a conversational AI provide a better way to control one’s feed?The “WordDJ” tool has no keyboard but lets you move blocks of text around like fridge magnets or combine them. The conversational agent allows users to describe more specifically what they’d like to see more or less of rather than muting accounts or the like.

Disclaimer – This is just shared content from above mentioned source for knowledge sharing.


Rollstack automatically syncs data to reports and presentations



Most white collar jobs involve creating presentations. And this can be a time-consuming, laborious process. Presentations include data points, and ensuring that these data points remain accurate and up to date is a challenging task in its own right.

A study from Coveo, in fact, has found that the stress and hassle of locating the right information in workplaces is causing employee burnout. Employees report spending nearly four hours each day searching for info; over 31% of those surveyed said the frustration of being unable to find information made them feel burned out.

To help ease the burden — at least on the data points front — Nabil Jallouli, Bahir Saad and Younes Jallouli co-founded Rollstack, a platform that automatically updates the metrics and figures in slide decks, reports and documents. A member of Y Combinator’s Winter 2023 cohort, Rollstack has raised $1.8 million in seed funding from investors including Y Combinator, UpHonest Capital, Kima Ventures, Monte Carlo Capital and Roosh Ventures.

“Recurring reporting isn’t just a task — it’s a cornerstone of teams’ decision-making processes,” Nabil told TechCrunch in an email interview. “Teams operate in a constant cycle of data extraction, synthesis and presentation, both for internal strategizing and external communications. Traditionally, this workflow has been labor-intensive, but Rollstack is specifically designed for these challenges.”


Image Credits: Rollstack

Prior to founding Rollstack, Nabil led data, strategy and revenue operations teams at Pinterest, Deel and Groupon. Bahir was a software and DevOps engineer at cashierless checkout startup AiFi, while Younes held various engineering and product positions at Tesla.

With Rollstack, Nabil, Bahir and Younes sought to create a tool that allows teams to automatically update their presentations using data sources like Tableau, Salesforce and Looker. Rollstack lets users connect to data sources – including business intelligence tools, customer relationship management (CRM) platforms and databases — and set up scheduled data and visualization refreshes for presentations and reports created with Google Slides, PowerPoint, Google Docs, Word or Notion.

Rollstack takes care of refreshing the data where it’s presented and saves formatting and visualization preferences for future use. In addition, it allows users to create new versions of the same deck programmatically, and implement version control to roll back to historical data snapshots (e.g. data from a previous fiscal year).

“These automations allow employees to concentrate on their core tasks like analysis, strategy or selling, rather than the tedious process of generating data reports,” Nabil said.

Rollstack has competition in Coefficient, which lets users create, share and automate live reports, set up alerts and write data back to connected software-as-a-service (SaaS) tools. Actiondesk similarly connects with databases, CRMs and SaaS tools to feed live data into Excel and Google Sheets spreadsheets. But Nabil points out that Rollstack supports a wide range of document types — wider than most of its rivals, he asserts.

Rollstack claims that its customer base is growing by 50% every month and includes companies ranging from startups to “large publicly-listed firms.” Nabil wouldn’t disclose revenue — or burn rate. But he said that Rollstack plans to double the size of its seven-person team by the end of Q1 2024.

“Manual work is Rollstack’s primary competitor,” he added. “With the team’s expertise in the field, Rollstack is well positioned to leverage AI to further enhance its clients’ efficiency. The focus remains on delivering real value and impact to its users — rather than just following trends.”

Disclaimer – This is just shared content from above mentioned source for knowledge sharing.

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Russian zero-day seller offers $20M for hacking Android and iPhones



A company that acquires and sells zero-day exploits — flaws in software that are unknown to the affected developer — is now offering to pay researchers $20 million for hacking tools that would allow its customers to hack iPhones and Android devices.

On Wednesday, Operation Zero announced on its Telegram accounts and on its official account on X, formerly Twitter, that it was increasing payments for zero-days in those platforms from $200,000 to $20 million.

“By increasing the premium and providing competitive plans and bonuses for contract works, we encourage the developer teams to work with our platform,” the company wrote.

Operation Zero, which is based in Russia and launched in 2021, also added that “as always, the end user is a non-NATO country.” On its official website, the company says that “our clients are Russian private and government organizations only.”

When asked why they only sell to non-NATO countries, Operation Zero CEO Sergey Zelenyuk declined to say. “No reasons other than obvious ones,” he said.

Zelenyuk also said that the bounties Operation Zero offer right now may be temporary, and a reflection of a particular time in the market, and the difficulty of hacking iOS and Android.

“The price formation of specific items is heavily dependent on availability of the product on the zero-day market,” Zelenyuk said in an email. “Full chain exploits for mobile phones are the most expensive products right now and they’re used mostly by government actors. When an actor needs a product, sometimes they’re ready to pay as much as possible to possess it before it gets into the hands of other parties.”

For at least a decade, various companies around the world have offered bounties to security researchers willing to sell the bugs and hacking techniques to exploit those flaws. Unlike traditional bug bounty platforms like Hacker One or Bugcrowd, companies like Operation Zero don’t alert the vendors whose products are vulnerable, but instead sell them to government customers.

This is inherently a gray market, where prices fluctuate and the identity of the customers is often secret. But there are and have been public price lists such as the ones published by Operation Zero.

Zerodium, a company that was launched in 2015, offers up to $2,5 million for a chain of bugs that allows customers to hack an Android device with no interaction from the target, meaning the target doesn’t have to fall for a phishing link, for example. For the same type of chain, Zerodium offers up to $2 million, according to its website.

On modern mobile devices, thanks to improved security mitigations and defenses, hackers might need a series of zero-days to fully compromise and take control of a targeted device.

Crowdfense, a competitor based in the United Arab Emirates, offers up to $3 million for the same kind of chain of bugs on Android and iOS.

Referring to the bounties offered by Zerodium and Crowdfense, Zelenyuk said that he doesn’t believe they will ever drop so low.

“The Zerodium price sheet is outdated, but it doesn’t mean the company still buys for such low prices. They just don’t need to update them, the zero-day business works fine regardless of that,” said Zelenyuk.

The market for zero-days is largely unregulated. But in some countries, companies may have to obtain export licenses from the governments they operate from. This process essentially entails asking permission to sell to certain countries, which may be restricted. This has created a fractured market that is increasingly affected by politics. For example, a recently passed law in China mandates that security researchers alert the Chinese government of bugs before they alert the software makers. This law, according to experts, effectively means China is cornering the market for zero-days in an attempt to use them for intelligence purposes.

“This new regulation might enable elements in the Chinese government to stockpile reported vulnerabilities toward weaponizing them,” Microsoft said in a report from last year.

Corrected an earlier version of this story to remove “tenfold” from the second paragraph, this was due to an editor’s error. ZW

Do you have more information about the market for zero-days? We’d love to hear from you. You can contact Lorenzo Franceschi-Bicchierai securely on Signal at +1 917 257 1382, or via Telegram, Keybase, and Wire @lorenzofb, or email You can also contact TechCrunch via SecureDrop.

Disclaimer – This is just shared content from above mentioned source for knowledge sharing.

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TC Startup Battlefield master class with Canvas Ventures: Creating strategic defensibility as an early-stage startup



Each year, TechCrunch selects the top 200 early-stage founders from across the globe to feature at TechCrunch Disrupt in San Francisco. And as part of our programming, we host master classes with industry experts and venture capitalists to provide tactical advice and insight to these founders.

Today, I’m excited to share the first of a four-part series with Canvas Ventures’ Mike Ghaffary. In this session, Ghaffary outlined the important components of startup defensibility, the key strategic advantage buckets, and what startups can do to stay competitive as they build and scale.

This private session took place in August, and we are sharing these now so all of you can also reap the benefits of Startup Battlefield.

Disclaimer – This is just shared content from above mentioned source for knowledge sharing.

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