Robotics & AI

Google introduces Workspaces Spaces Chats conversations summaries • ZebethMedia

By zebethcontrolPosted on November 18, 2022Posted in Enterprise, Google, Robotics & AI, summarizationNo Comments

Having trouble keeping up with the conversations in your Chats in your Workspace Spaces? Google feels your pain, and is “excited to introduce conversation summaries in Google Chat for messages in Spaces.” Now your conversations in Spaces Chats will be summarized right in your Premium Workspace. The issue is, of course, that while Chats in Spaces are perfectly good for conversations, in larger Workspaces these Chats conversations can be difficult to keep up with unless you’re always checking your Spaces for new conversations in Chats. You know the drill – you log into your Workspace, click over to your Spaces, pull up the Chats, and your conversations are just too numerous and long-winded to catch up on! You can’t very well tell your Workspace Spaces conversationalists to leave off chatting in your Chats. Conversation is the very reason Chats exist, that’s why they call it Spaces! I mean Chats! Fortunately Google is bringing its expertise in communications apps to remedy this conversational crisis in your Workspace Spaces Chats. Starting soon, the messages in your conversations will be summarized right in your Chats, inside Spaces in Workspaces! Selected Premium Workspaces, anyway. Google put a summary in your Premium Workspace Spaces Chat conversations. You read that correctly. The Conversation Summary of the messages in your Workspace Spaces Chat will appear at the top of the Chats within Spaces, summarizing any unread chatter in the Chats conversation. Click on the summary of the Spaces Chats and you’ll jump straight to the conversation, even if it’s already visible and the Conversation summary has only summarized a few lines of the Chats conversation. If you use Spaces in your Workspace, and tend to have conversations in the Chats of those Spaces, Conversation Summary in Google Chat could be just the thing to keep those chatty Chats summarized. Sadly, this doesn’t appear to be available for Google Chat, though — which is to say regular Google Chat (that is, the newish one in your Gmail that used to be Hangouts, possibly), only Google Chat for Spaces in Workspaces, and (don’t forgot) select Premium Workspaces at that. Definitely not Meet messaging. So you probably don’t have access. But you might eventually, if Workspace Spaces Chats are still something that exist in six months. (I’m checking with Google on this.) Check out the technical details on how the Google AI team quickly and effectively summarizes conversations in Chats in Spaces in Workspaces right here. 🙂

Soft Robotics raises $26 million as staffing shortages continue • ZebethMedia

By zebethcontrolPosted on November 17, 2022Posted in Hardware, Robotics & AI, Soft Robotics, Tyson VenturesNo Comments

I spent last week in Boston, meeting with several of the area’s top automation startups. Soft Robotics — based in nearby Bedford, Massachusetts — is one of those names that comes up a lot. As the concept of soft robotics grippers have increasingly come into vogue, the company of the same name has been reaping much of that windfall. Today, for instance, it announced a $26 million Series C, led by Tyson Ventures. The VC arm of Tyson Foods is a natural fit here. After all, food production has long been a big piece of Soft Robotics’ strategy. Its compliant grippers do a good job picking up fragile and inconsistently sized foodstuffs, from meat to produce — a longstanding challenge for more rigid systems. “At Tyson, we are continually exploring new areas in automation that can enhance safety and increase the productivity of our team members,” Tyson Ventures’ Rahul Ray said in a release. “Soft Robotics’ revolutionary robotic technology, computer vision and AI platform have the potential to transform the food industry and will play a key role in any company’s automation journey.” Marel and Johnsonville also joined the round as new investors, following a $23 million Series B with a $10 million extension raised in June of last year. At the time, Soft Robotics cited pandemic-fueled job loss as a major motivator in the funding round. Obviously the job situation hasn’t gotten much better — particularly in industries like meat packing — even as funding has largely slowed down across the board over the past year. The firm says the new round of funding will go toward accelerating the deployment of its mGripAI system, which combines 3D vision with a soft gripping system. Soft Robotics says the perfect storm of pandemic-fueled issues has resulted in “the four largest sales quarters in the company’s eight-year history.”

Scene Report: Boston • ZebethMedia

By zebethcontrolPosted on November 17, 2022Posted in amazon robotics, boston, Hardware, MassRobotics, Robotics & AI, Tye BradyNo Comments

What surprised me most on returning to Boston* for the first time since the onset of the pandemic was just how clustered things are. I’m not a great scheduler and I don’t know the city’s geography particularly well, but after two days spent meeting with more than a dozen startups, it slowly dawned on me that I was mostly operating within a five- to ten-block radius a stone’s throw from MIT (and, for that matter, Harvard). I’d given myself a little breathing room between meetings and site visits on Friday and was able to walk to all my meetings (the unseasonably warm weather didn’t hurt) — passing several of the spots I’d visited for conversations two days prior. Much like Pittsburgh, Boston has a tight-knit startup community. As companies get bigger, they’ll move to places like Waltham and Bedford on the outskirts, but they’ll remain part of this community nonetheless. There are several reasons I can see, as an outsider with only passing familiarity: It’s less sprawling than a place like the Bay Area/Silicon Valley or New York. The startups are often the outgrowth of universities (MIT, Harvard, Northeastern, BU), and there’s a built-in camaraderie there. Most people have worked at iRobot at some point. That last one’s diversifying a bit. Big corporations like Amazon (which may soon absorb iRobot) and Google have moved in as well. But the fact remains that most people aren’t ready to launch a startup right out of college, and these sorts of bigger corporations can be a good place to establish yourself and get a lay of the land. (Though universities are now doing an increasingly good job providing startup resources and accelerating companies after graduation.) Much like my own industry, everyone sort of knows everyone else, whether personally or by reputation. The longer you stay in a relatively insular industry, the more you’ll find yourself working with the same people time and again, so definitely try not to be an asshole (good advice generally, but doubly so when there can be clear and immediate consequences). You’re going to cross paths with the same people over and over. Life is funny like that. *I had drinks with a friend on Friday who helpfully noted that not every local is thrilled at the idea of using Boston, Cambridge, Somerville and the like interchangeably. So I’m going to just have to ask forgiveness rather than permission as I attempt to get this newsletter out in a timely fashion. I understand the importance of regional distinctions, as someone who has spent the majority of his life living in both the San Francisco Bay Area and two New York City boroughs, but for the sake of expediency in a very long newsletter, let’s assume all mentions of Boston are a reference to the city’s greater metropolitan area. World’s widest cable stayed bridge crossing the Charles River. Completed 2002. Image Credits: Getty Images / John Coletti This struck me the first time ZebethMedia did a small dinner ahead of our first Robotics event. Everyone knew everyone else. And most of them had been through the ranks of iRobot at one point or another. It’s not quite the Willow Garage story, but it’s another very clear case of a hub with a lot of important spokes. It also points to — as numerous people rightfully reminded me over the past week — the fact that we’re still very much in the early days of robotics. It feels like a small community because it is one, in a lot of ways. That’s exciting. I’ve spent much of my life feeling like I was a bit lately to different parties, but robotics feels new and fresh because it is. Some folks point to the home-brewed computer revolution that pulled in Steve Jobs and Bill Gates as a helpful way to contextualize where we are on the timeline. Others (like Tye Brady below) point significantly further back. I don’t think there’s a direct analog, but I do believe that 15 or 20 years from now, people will fondly remember this as a golden age for robotic discovery. The energy is palpable when you visit these sites. Much of Silicon Valley has spent the last decade trying to reengineer the same handful of tired apps over and over again (that’s not to say it’s all bad, but there’s a kind of stasis that comes with maturity). Here, however, you can talk to a million people chasing down real-world problems. The speed and excitement at which many of these breakthroughs occur can be head spinning. Of course, it’s important to remember that they’re standing on the backs of decades of research. Practically every technical founder has some university professor they’ll happily tell you is one of the great unsung heroes of robotics and AI. This, I think, is a big part of the reason why many robotics firms have set up a kind of miniature museum near the building’s entrance. It serves to show how far you’ve come, while providing a tangible connection to where you came from. Many of the products found on these shelves are a jumble of hastily soldered wires and 3D-printed parts. They’re the results of the excitement that drives people to build things with their hands in an effort to prove out whiteboarded theses. You want to bottle that jolt of electricity you get from the first time a scrappy bit of hardware works as intended and mete it out in those times when businesses become a hard slog and you lose sight of that original vision. Image Credits: Rise Robotics I should add here that pivoting doesn’t necessarily qualify as losing sight. It’s extremely common in robotics. You set out to solve a specific problem and find yourself suddenly deeply immersed in another thing entirely. A prime example of that from last week is the team at Rise Robotics, which started life as an exosuit company and is now making massive actuators for heavy machinery. Perhaps the most

Ghost Robotics fires back against ‘baseless’ Boston Dynamics lawsuit • ZebethMedia

By zebethcontrolPosted on November 17, 2022Posted in boston dynamics, ghost robotics, Hardware, Robotics & AINo Comments

A legal dispute over robotic patents is devolving into a war of words, as Ghost Robotics fires back against Boston Dynamics. The Philadelphia firm calls the suit both “obstructive and baseless” in a statement sent to ZebethMedia. It notes, in part, Ghost Robotics’ success has not gone unnoticed by Boston Dynamics. Rather than compete on a level playing field, the company chose to file an obstructive and baseless lawsuit on November 11th in an attempt to halt the newcomer’s progress. Boston Dynamics is drawing on their considerably larger resources to litigate instead of innovate. Ghost’s statement, in which it refers to itself as “the number one supplier of legged robots to US and Allied Governments,” follows press reports of a lengthy suit filed by Boston Dynamics in a Delaware court. It adds that the company has its roots in its own legged robotic research, writing, “Ghost Robotics was born out of the PhD research of CTO Avik De and CEO Gavin Kenneally, under the tutelage of the esteemed Prof. Dan Koditschek at The University of Pennsylvania. Prof. Koditschek is a pioneer in the field of legged robots and holds the patent (jointly with his former students, Martin Buehler and Uluc Saranli) for the first battery-powered, dynamic legged robot, RHex (US6481513B2, filed March 14, 2001).” On Tuesday, Spot’s maker told ZebethMedia that it doesn’t comment on pending lawsuits, but added, Innovation is the lifeblood of Boston Dynamics, and our roboticists have successfully filed approximately 500 patents and patent applications worldwide. We welcome competition in the emerging mobile robotics market, but we expect all companies to respect intellectual property rights, and we will take action when those rights are violated. In the suit, Boston Dynamics cites multiple letters, including cease and desists, calling on Ghost to suspend the manufacture of its own four-legged dog robots over several alleged patent violations. It’s not the first time to two companies have butted heads. Ghost made national headlines after images surfaced of one of its dog robots sporting a SWORD Defense Systems Special Purpose Unmanned Rifle (SPUR). A drawing from Boston Dynamics’ suit The company’s then-CEO Jiren Parikh (who passed away in March of this year) told ZebethMedia at the time, We don’t make the payloads. Are we going to promote and advertise any of these weapon systems? Probably not. That’s a tough one to answer. Because we’re selling to the military, we don’t know what they do with them. We’re not going to dictate to our government customers how they use the robots. We do draw the line on where they’re sold. We only sell to U.S. and allied governments. We don’t even sell our robots to enterprise customers in adversarial markets. We get lots of inquiries about our robots in Russia and China. We don’t ship there, even for our enterprise customers. Last month Boston Dynamics joined a number of follow robotics firms in an open letter condemning the practice of weaponizing robotics. The letter notes, in part, We believe that adding weapons to robots that are remotely or autonomously operated, widely available to the public, and capable of navigating to previously inaccessible locations where people live and work, raises new risks of harm and serious ethical issues. Weaponized applications of these newly-capable robots will also harm public trust in the technology in ways that damage the tremendous benefits they will bring to society. Boston Dynamics is seeking unspecified damages in its suit.

Speak lands investment from OpenAI to expand its language learning platform • ZebethMedia

By zebethcontrolPosted on November 17, 2022Posted in Apps, funding, language learning, OpenAI Startup Fund, Robotics & AI, SPEAK, startup, StartupsNo Comments

Speak, an English language learning platform with AI-powered features, today announced that it raised $27 million in a Series B funding round led by the OpenAI Startup Fund, with participation from Lachy Groom, Josh Buckley, Justin Mateen, Gokul Rajaram and Founders Fund. Notably, Speak is the third startup in which OpenAI, the AI lab closely aligned with Microsoft, has publicly invested through its fund — the others being Descript and Mem. OpenAI Startup Fund participants receive early access to new OpenAI systems and Azure resources from Microsoft in addition to capital. “We are very excited to partner with the outstanding team at Speak, who are well-positioned to deliver on this powerful application of generative AI — making language learning effective and accessible,” Brad Lightcap, OpenAI’s COO and the manager of the OpenAI Startup Fund, said in a statement. “Speak has the potential to revolutionize not just language learning, but education broadly, and this aligns with the OpenAI Startup Fund’s goal of accelerating the impact of powerful AI to improve people’s lives.” Speak was founded in 2016 by Connor Zwick and Andrew Hsu, both of whom had an acute interest in AI from an early age. Hsu has a health background, having completed a neuroscience PhD at Stanford before joining Zwick to co-launch Speak. Zwick came from the edtech industry — he sold his first startup, the flashcard app Flashcards+, to Chegg in 2013 after dropping out of Harvard. Zwick and Hsu met through The Thiel Fellowship originally, Hsu being in the first cohort and Zwick in the second. (Note that Founders Fund, which Thiel co-founded, pledged cash toward Speak’s Series B.) Prior to starting Speak, the two spent a year studying and researching machine learning and developing accent detection algorithms using YouTube videos as training data. “Most language learning software can help with the beginning part of learning basic vocabulary and grammar, but gaining any degree of fluency requires speaking out loud in an interactive environment,” Zwick told ZebethMedia in an email interview. “To date, the only way people can get that sort of practice is through human tutors, which can also be expensive, difficult and intimidating.” Image Credits: Speak Speak’s solution is a collection of interactive speaking experiences that allow learners to practice conversing in English. Through the platform, users can hold open-ended conversations with an “AI tutor” on a range of topics while receiving feedback on their pronunciation, grammar and vocabulary. The premise might sound like Duolingo and some of the other AI-powered language learning apps out there, such as Yanadoo, ELSA and Loora. But Zwick insists that Speak’s AI tech is superior to most. “Under the hood, we combine the latest from OpenAI with in-house models to deliver the best performance across speech recognition, speech generation and conversation generation,” he said. “We’re able to provide feedback on things like pronunciation and more natural vocabulary and syntax using [our] models … We are accumulating a substantial data set of second-language labeled speaking examples, which enables us to uniquely deliver state-of-the-art speech models for foreign accented speakers.” Whether that’s true is up for debate. Speak didn’t provide any empirical data showing its platform outperforms rivals. But what Speak does demonstrably have is early momentum. It’s one of the top education apps in Korea on the iOS App Store, with over 15 million lessons started annually, 100,000 active subscribers and “double-digit million” annual recurring revenue. Speak offers auto-renewing monthly and annual subscriptions, both of which provide access to courses, electives and review content in addition to the AI-guided practice sessions. For Speak’s next act, the company plans to expand to new languages and markets, including Japan, and invest in features that leverage text-generating models like OpenAI’s GPT-3. “The pandemic accelerated remote work and the expansion of global, distributed teams, meaning there’s even more demand for people around the world to speak the same language. It’s also driven demand for new solutions more oriented around remote or programmatic experiences as opposed to in-person instruction.” Zwick added. “Speak has remained fairly lean and has multiple years of runway enabling it to control its own destiny regardless of the fundraising environment over the next few years.” Currently, Speak has 40 employees across offices in San Francisco (its headquarters), Seoul and Ljubljana, Slovenia. Zwick says that the new funding, which brings Speak’s total raised to “just over” $47 million, will be put toward expanding the company’s engineering, machine learning, product, marketing, content and operations departments.

Terzo lands $16M to extract key data from contracts • ZebethMedia

By zebethcontrolPosted on November 17, 2022Posted in AI, Enterprise, funding, Robotics & AI, startup, StartupsNo Comments

Contract governance is the steps taken to make sure agreed-upon terms between a company and its suppliers are met. It’s an essential part of doing business, and the consequences for getting it wrong can be steep. McKinsey estimates that poor contract governance can cost organizations up to 9% of their total revenue, which equates to $1.4 trillion for the Fortune 500 alone and $6.4 trillion across all enterprise business-to-business companies. Challenges around contract governance have fueled the rise of startups like Icertis, which recently secured $150 million at a $3.2 billion valuation to build out its contracting tools. LinkSquares in April landed $100 million for its AI-powered contract analysis platform, while ContractPodAi, a close competitor, has raised tens of millions to digitize contract reviews. A relatively new entrant in the space is Terzo, which was co-founded by Brandon Card, Al Giocondi and Pradeep Thangavel in 2020. A suite of contract processing software, Terzo uses AI to extract data in contracts related to a company’s spend and revenue across their supplier and customer relationships. In a sign investor interest in contract management startups hasn’t waned, Terzo today closed a $16 million Series A round led by Align Ventures with participation from TYH Ventures, Engage Ventures, Human Capital and other unnamed institutional investors. The proceeds bring the company’s total raised to more than $18f million, and Card, who serves at Terzo’s CEO, says they’ll be put toward Terzo’s sales and marketing initiatives as well as enhancing the platform’s AI capabilities. “As our technology evolves, we aim to deliver advanced insights around financials and budgeting,” Card said. “Contract systems were built for legal use cases and legal teams to focus on drafting and clauses. There are no analytics or financial insights for leaders to make smarter decisions. Terzo was founded to solve that problem.” Image Credits: Terzo Card says his experiences at Microsoft, where he was an enterprise portfolio manager at Microsoft Cloud, inspired him to co-found Terzo. Giocondi came from account manager roles at Oracle and IBM. As for Thangavel, he spent nearly seven years on the engineering side at Freshworks prior to joining alongside Card and Giocondi. Card says that Terzo’s AI was trained using real-world business contracts to extract data such as inventory and costs, supervised by a quality assurance team to ensure baseline accuracy. Terzo integrates with enterprise resource platforms like SAP and Oracle to track contractual obligations and expiration dates, including metrics related to environmental, social and governance policies. “Terzo is valuable to the IT audience because it allows them to see data faster,” Card said. “We’ve created a platform that combines data management, automation and AI, but also keeps people in the loop.” VCs see promise in contract management legal tech like Terzo’s, perhaps in part because of the high customer adoption rate. According to a 2020 Bloomberg Law survey, more than half (56%) of in-house lawyers said that they’re using contract management programs. (That’s despite the fact that the legal industry is notoriously slow to adopt new tech.) If the current trend holds, Markets and Markets predicts the contract management life cycle market will grow from $1.5 billion in 2019 to $2.9 billion by 2024. Card says that Terzo has “over a dozen” customers, including a Fortune 50 retailer and the largest financial transaction processor in the world. The plan into the next year is to drive revenue at over 50% of Terzo’s overall expenses, he says, and to break even in 2024. “We are positioned to be a profitable business by 2025,” Card added. “Both the pandemic and current tech slowdown has taught us how to run a lean business that is focused on efficient growth. The current downturn has caused our customers to prioritize spending and budgeting so we look at this as a positive tailwind heading into 2023.”

Namecoach raises cash to teach users how to correctly pronounce names • ZebethMedia

By zebethcontrolPosted on November 17, 2022Posted in AI, Enterprise, funding, Robotics & AI, startup, StartupsNo Comments

We’ve all been faced with a name that’s difficult to pronounce. But not everyone considers the consequences of their mispronunciations. In a piece for Fast Company, Madhumita Mallick, the head of inclusion, equity and impact at Carta, recalls how her name became a source of anxiety even when she was a grade-school student. Studies have indeed found that when peers and teachers incorrectly pronounce or change the names of students of color, those students participate less in class and becoming socially withdrawn to avoid associating with their name. As the co-authors of one wrote in 2012: “actions and attitudes [students] experienced in K-12 schools highlight a type of cultural ‘othering’ that contradicts our goals for multicultural school environments .. even just stumbling over a name they had never seen before, the tone set by a teacher about a student’s name [is] something significant.” Praveen Shanbhag, the CEO of Namecoach, heard a speaker at his sister’s alma mater flub her name during her college graduation. That, along with his experiences as a first-generation immigrant to the U.S., inspired him to co-found Namecoach, which develops name pronunciation tools that can be embedded in existing platforms like Salesforce, Canvas and Gmail. “We are on a mission to make name mispronunciation a thing of the past for everyone,” Shanbhag told ZebethMedia via email. Shanbhag started dabbling in programming while working on his Ph.D. in philosophy at Stanford. He decided to code an app that would collect recordings of students saying their names and deliver them to name readers for graduation, which became Namecoach. By 2016, Shanbhag says that hundreds of schools were using Namecoach’s software and services. Namecoach — which eventually broadened its customer base to client brands — isn’t alone in the market. NameShouts offers a robust set of name pronunciation tools, as does Facebook, Slack and LinkedIn. But Shanbhag tells me that early on, he sought to differentiate Namecoach by investing heavily in AI and integrations. Image Credits: Namecoach For example, Namecoach uses an AI system to predict the correct pronunciation when someone’s name has multiple correct pronunciations based on factors like nationality, ethnicity, gender and location. Another of the platform’s systems synthesizes speech in situations where an audio recording of a name isn’t available. At a high level, Namecoach shows name pronunciations both user-generated and drawn from a database of audio name pronunciations. When asked about the system’s accuracy and whether users can remedy mistakes that might make their way onto the database, Shanbhag said that Namecoach consults with linguistic experts and offers a submission form for corrections. It’s not yet live, but Shanbhag says that Namecoach is developing a AI to provide pronunciations that take the speaker’s native language into account — not just the name-owner’s language. “Your name is central to your identity, and accurate pronunciation sets the tone for a positive interaction for both parties,” he said. Namecoach’s platform works out-of-the-box with services including Microsoft Teams, Outlook and Google Workspace and offers an API and software development kit to let third parties build Namecoach’s functionality into their products. But the focus over the next few months will be the startup’s first-ever consumer app, Shanbhag says, which will be made available as a Chrome extension next year. Namecoach — which today closed an $8 million Series A round led by Impact America Fund with participation from Authentic Ventures, Metaplanet, Engage.VC, Founders Fund, Bisk Ventures and others — also plans to ramp up its sales and marketing efforts and expand the platform’s collection of connectors. Shanbhag hinted at capabilities beyond pronunciation guidance coming down the pipeline, including prompts to enable warm interactions in sales scenarios and feedback to help users improve their conversations more generally. Leaning into sales applications makes sense given Namecoach’s marquee customers — Salesforce, Netjets and PwC. Beyond those three, the 30-person startup claims to have more than 300 education and corporate clients worldwide. “The Series A funding enables us to accelerate our goal of integrating novel voice technology into every communication workflow to solve name pronunciation across a wide spectrum of use cases during any voice interaction,” said Shanbhag, who wouldn’t Namecoach’s disclose revenue figures when asked. “Namecoach has customers across a very wide range of verticals, use cases and organization size, which means that we are not reliant on any subsegment to thrive in a downturn.” To date, Palo Alto-based Namecoach has raised $15 million in venture capital.

With fresh capital, Symend aims to build a better debt collection system • ZebethMedia

By zebethcontrolPosted on November 17, 2022Posted in BDC Growth Venture Co-Investment Fund, BDC Women in Technology Fund, debt collection, EDC, Fintech, funding, Growth Venture Co-Investment Fund, Impression Ventures, iNovia Capital, Mistral Venture Partners, Plaza Ventures, Robotics & AI, startup, Startups, symend, Women in Technology FundNo Comments

Squeezed by the recessionary COVID-19-era economy and the rising prices of everyday goods, some consumers are increasingly turning to lines of credit to make ends meet. According to a September 2021 survey from Bankrate.com, 42% of U.S. adults with credit card debt increased their balances since the pandemic began in March 2020. A more recent report from the Federal Reserve Bank of New York estimates that total household debt in Q3 2022 reached $16.51 trillion, $2.36 trillion higher than at the end of 2019. The New York Fed’s study also showed that the share of current debt becoming delinquent climbed for nearly all debt types, from mortgages to auto loans. But even before the pandemic and crippling inflation struck, the U.S. had a delinquent debt problem. A 2016 whitepaper from the Association of Credit and Collection Professionals International found that debt rose from $150 billion to over $600 billion in the previous five years. During the same timeframe, collection agencies — who take between 20% to 50% of money recovered — had an annual success rate of 7%. To solve it — an ambitious goal, to be sure — Hanif Joshaghani and Tiffany Kaminsky co-founded Symend, a company that employs AI and machine learning to automate processes around debt resolution for telcos, banks and utilities. Symend today announced that it raised $42 million in a Series C round led by Inovia Capital with participation from Impression Ventures, Mistral Venture Partners, BDC’s Growth Venture Co-Investment Fund, BDC Capital’s Women in Technology Fund, Plaza Ventures and EDC. While substantially smaller than Symend’s once-extended Series B round ($95 million), Joshaghani, Symend’s CEO, noted that it’s “all equity” and brings the company’s total capital raised to date to $140 million. “We have maintained and continue to maintain a very conservative balance sheet profile,” Joshaghani told ZebethMedia in an email interview. “This latest injection of growth capital allows us to meet the growing demand for our behavioral engagement technology around the world. While this is not an optimal time for many businesses to turn to funding, for Symend, this was an ideal time as our product demand rises and the realities of the market create a deepening white space for us to capture.” Joshaghani hails from the financial industry, having worked as a corporate finance manager and investment banking association. Kaminsky’s background is marketing — prior to co-founding Symend, she was the head of sales and marketing strategy at Frog3D, a CNC fabrication business. Examples of messages customers might see from brands working with Symend. Both Joshaghani and Kaminsky personally experienced the negative impact of debt, they say. Joshaghani grew up in a household frequently targeted by calls from debt collectors, and Kaminksi ran into trouble with collections with her first credit card as a young adult. “To this day, I remember the anxiety I felt when receiving calls from collections and knew there had to be a better way — both for customers and businesses,” Joshaghani said. “We founded Symend to help consumers like us and as we’ve grown over the past six years, that mission has remained the same — our vision is to transform the science of engagement on a global scale.” Symend identifies when customers are having trouble paying bills and provides analytics and tools aimed at helping companies develop debt remediation programs. Via the platform’s workflows, businesses can engage with nearly-delinquent customers at points likeliest to drive turnaround. For example, they can configure Symend to create payment plans and limited-time payment discounts for certain segments of customers, or they can have the platform connect at-risk customers with financial planning tools, resources and credit rehabilitation programs. As Joshaghani explained to me, Symend works with a company’s existing systems to “optimize engagement” with customers falling behind on bills due to illness, job loss, family trouble and other foreseen and unforeseen circumstances. The platform allows a business to send “hyper-personalized” messages via a customer’s preferred channels (e.g. text and email) while providing that business access to playbooks for various debt collection scenarios (e.g., delinquent credit card). “Our clients continue to use general-purpose engagement platforms to manage their broad-based customer communications but deploy Symend specifically to solve complex challenges around their past-due customer base,” Joshaghani said. “Our ability to productize behavioral science is one of three key innovation areas of our technology, which uses AI, machine learning and data science to develop proven behavioral engagement playbooks to deliver impact out-of-the-box for companies in various industries.” Symend is rather vague about the functionality and technical underpinnings of its platform — its website prefers jargony buzzwords to plain-English descriptions. But that hasn’t scared away customers, it’d seem; Joshaghani claims that Symend is currently serving financial institutions, alternative lenders, utility companies and the majority of telecom providers in North America, including Telus. No doubt, the rise in buy now, pay later (BNPL) services — which let users split up purchases into equal installments over a fixed short-term period — is driving new business to Symend. A recent U.S. Consumer Financial Protection Bureau report found that delinquencies on BNPL services are rising sharply as vendors approve more customers for loans. “As with many businesses right now, the current market conditions and economic uncertainty has led to us seeing clients with tighter budgets and streamlined decision-making,” Joshaghani added. “However, this latest funding highlights the market need, growing consumer demands for an empathetic, personalized approach as consumers face financial stress, and investor confidence in the company’s proven track record with some of the largest financial institutions and telecommunications providers during a time where every dollar and customer has become more important than ever.”

Protein programmers get a helping hand from Cradle’s generative AI • ZebethMedia

By zebethcontrolPosted on November 17, 2022Posted in Biotech & Health, cradle, Generative AI, machine learning, proteomics, Robotics & AI, StartupsNo Comments

Proteins are the molecules that get work done in nature, and there’s a whole industry emerging around successfully modifying and manufacturing them for various uses. But doing so is time consuming and haphazard; Cradle aims to change that with an AI-powered tool that tells scientists what new structures and sequences will make a protein do what they want it to. The company emerged from stealth today with a substantial seed round. AI and proteins have been in the news lately, but largely because of the efforts of research outfits like DeepMind and Baker Lab. Their machine learning models take in easily collected RNA sequence data and predict the structure a protein will take — a step that used to take weeks and expensive special equipment. But as incredible as that capability is in some domains, it’s just the starting point for others. Modifying a protein to be more stable or bind to a certain other molecule involves much more than just understanding its general shape and size. “If you’re a protein engineer, and you want to design a certain property or function into a protein, just knowing what it looks like doesn’t help you. It’s like, if you have a picture of a bridge, that doesn’t tell you whether it’ll fall down or not,” explained Cradle CEO and co-founder Stef van Grieken. “Alphafold takes a sequence and predicts what the protein will look like,” he continued. “We’re the generative brother of that: you pick the properties you want to engineer, and the model will generate sequences you can test in your laboratory.” Predicting what proteins — especially ones new to science — will do in situ is a difficult task for lots of reasons, but in the context of machine learning the biggest issue is that there isn’t enough data available. So Cradle originated much of its own data set in a wet lab, testing protein after protein and seeing what changes in their sequences seemed to lead to which effects. Interestingly the model itself is not biotech-specific exactly but a derivative of the same “large language models” that have produced text production engines like GPT-3. Van Grieken noted that these models are not limited strictly to language in how they understand and predict data, an interesting “generalization” characteristic that researchers are still exploring. Examples of the Cradle UI in action. The protein sequences Cradle ingests and predicts are not in any language we know, of course, but they are relatively straightforward linear sequences of text that have associated meanings. “It’s like an alien programming language,” van Grieken said. Protein engineers aren’t helpless, of course, but their work necessarily involves a lot of guessing. One may know for sure that among the 100 sequences they are modifying is the combination that will produce The model works in three basic layers, he explained. First it assesses whether a given sequence is “natural,” i.e. whether it is a meaningful sequence of amino acids or just random ones. This is akin to a language model just being able to say with 99 percent confidence that a sentence is in English (or Swedish, in van Grieken’s example), and the words are in the correct order. This it knows from “reading” millions of such sequences determined by lab analysis. Next it looks at the actual or potential meaning in the protein’s alien language. “Imagine we give you a sequence, and this is the temperature at which this sequence will fall apart,” he said. “If you do that for a lot of sequences, you can say not just, ‘this looks natural,’ but ‘this looks like 26 degrees Celsius.’ that helps the model figure out what regions of the protein to focus on.” The model can then suggest sequences to slot in — educated guesses, essentially, but a stronger starting point than scratch. And the engineer or lab can then try them and bring that data back to the Cradle platform, where it can be re-ingested and used to fine tune the model for the situation. The Cradle team on a nice day at their HQ (van Grieken is center). Modifying proteins for various purposes is useful across biotech, from drug design to biomanufacturing, and the path from vanilla molecule to customized, effective and efficient molecule can be long and expensive. Any way to shorten it will likely be welcomed by, at the very least, the lab techs who have to run hundreds of experiments just to get one good result. Cradle has been operating in stealth, and now is emerging having raised $5.5 million in a seed round co-led by Index Ventures and Kindred Capital, with participation from angels John Zimmer, Feike Sijbesma, and Emily Leproust. Van Grieken said the funding would allow the team to scale up data collection — the more the better when it comes to machine learning — and work on the product to make it “more self-service.” “Our goal is to reduce the cost and time of getting a bio-based product to market by an order of magnitude,” said van Grieken in the press release, “so that anyone – even ‘two kids in their garage’ – can bring a bio-based product to market.”

Tatum is building a robot arm to help people with deafblindness communicate • ZebethMedia

By zebethcontrolPosted on November 16, 2022Posted in accessibility, Hardware, robotics, Robotics & AI, Tatum RoboticsNo Comments

Precise numbers on deafblindness are difficult to calculate. For that reason, figures tend to be all over the place. For the sake of writing an intro to this story, we’re going to cite this study from the World Federation of the DeafBlind that puts the number of severe cases at 0.2% globally and 0.8% of the U.S. Whatever the actual figure, it’s safe to say that people living with a combination of hearing and sight loss is a profoundly underserved community. They form the foundation of the work being done by the small robotics firm, Tatum (Tactile ASL Translational User Mechanism). I met with the team at MassRobotics during a trip to Boston last week. The company’s 3D-printed robotic hand sat in the middle of the conference room table as we spoke about Tatum’s origins. The whole thing started life in summer 2020 as part of founder Samantha Johnson’s master’s thesis for Northeastern University. The 3D-printed prototype can spell out words with American Sign Language, offering people with deafblindness a window to the outside world. From the user’s end, it operates similarly to tactile fingerspelling. They place the hand over the back of the robot, feeling its movements to read as its spells. When no one is around who can sign, there can be a tremendous sense of isolation for people with deafblindness, as they’re neither able to watch or listen to the news and are otherwise cut off from remote communication. In this age of teleconferencing, it’s easy to lose track of precisely how difficult that loss of connection can be. Image Credits: Tatum Robotics “Over the past two years, we began developing initial prototypes and conducted preliminary validations with DB users,” the company notes on its site. “During this time, the COVID pandemic forced social distancing, causing increased isolation and lack of access to important news updates due to intensified shortage of crucial interpreting services. Due to the overwhelming encouragement from DB individuals, advocates, and paraprofessionals, in 2021, Tatum Robotics was founded to develop an assistive technology to aid the DB community.” Tatum continues to iterate on its project, through testing with the deafblind community. The goal to build something akin to an Alexa for people with the condition, using the hand to read a book or get plugged into the news in a way that might have otherwise been completely inaccessible. In addition to working with organizations like the Perkins School for the Blind, Tatum is simultaneously working on a pair of hardware projects. Per the company: The team is currently working on two projects. The first is a low-cost robotic anthropomorphic hand that will fingerspell tactile sign language. We hope to validate this device in real-time settings with DB individuals soon to confirm the design changes and evaluate ease-of use. Simultaneously, progress is ongoing to develop a safe, compliant robotic arm so that the system can sign more complex words and phrases. The systems will work together to create a humanoid device that can sign tactile sign languages. Image Credits: Tatum Robotics Linguistics: In an effort to sign accurately and repeatably, the team is looking to logically parse through tactile American Sign Language (ASL), Pidgin Signed English (PSE) and Signed Exact English (SEE). Although research has been conducted in this field, we aim to be the first to develop an algorithm to understand the complexities and fluidity of t-ASL without the need for user confirmation of translations or pre-programmed responses. Support has been growing among organizations for the deafblind. It’s a community that has long been underserved by these sorts of hardware projects. There are currently an estimated 150 million people with the condition globally. It’s not exactly the sort of total addressable market that gets return-focused investors excited — but for those living with the condition, this manner of technology could be life changing.