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Robotic Automations

Carbonfact is a carbon management platform designed specifically for the fashion industry | TechCrunch

April 30, 2024 10:47 AM0


French startup Carbonfact believes that the best carbon accounting solutions will focus on one vertical. That’s why the company has decided to provide a carbon management and reporting tool for the fashion industry exclusively.

And Carbonfact recently raised a $15 million funding round led by Alven, the French VC firm that led Carbonfact’s seed round in 2022 already. Other investors in the round include Headline and a follow-on investment from Y Combinator.

Big companies in the fashion industry (and other industries) need to come up with a carbon accounting strategy as regulation is changing in Europe and the U.S. with the EU’s Corporate Sustainability Reporting Directive (CSRD), California’s Climate Corporate Data Accountability Act and the NY Fashion Act.

That’s why there has been a boom in carbon accounting platforms. The biggest ones like Watershed, Persefoni, Sweep or Greenly have an industry-agnostic approach. They help you track your carbon emissions and create reports in a more or less automated way.

Just like Carbon Maps focuses exclusively on the food industry, Carbonfact is focusing on the fashion industry so that its product can be more granular and more specific.

“For these industries – food is a very good example, fashion is a very good example – you need to be accurate in your calculations and you need industry-specific tools to model virtual products and improve your product offering in the future,” Carbonfact co-founder and CEO Marc Laurent told me.

Carbon data at a product level

In more practical details, Carbonfact retrieves your existing data from your ERP and other internal systems. It then calculates the footprints for each product using a lifecycle assessment engine that is specifically designed for clothing items.

“[Clients] also have data in what they call PLM [Product Lifecycle Management software ] — that’s the software in which they put all the product data. This is where you’ll find the product recipe sheets. And they sometimes have data in traceability platforms, such as Retraced, Trustrace, Fairly Made in France, etc. And finally, they sometimes have data in Excel files,” Laurent said.

After centralizing and normalizing all data in a single platform, as the fashion industry relies on a cascade of suppliers, Carbonfact wants to help you calculate your scopes 1, 2 and 3 emissions — scope 3 emissions in particular encompass indirect emissions from third-party suppliers.

The startup first gives you a broad idea of your main emission hotspots with an uncertainty range. It then helps you prioritize data collection with your suppliers to refine your data and improve your carbon reporting.

After that, Carbonfact can become your carbon footprint dashboard. You can generate broad reports and drill down at an SKU-based level to see the environmental cost of each product. The platform can then be used to run what-if scenarios to see if you should change a material, move to a new country of manufacturing or change your transport methods.

Image Credits: Carbonfact

While many companies will focus first on CO2-equivalent metrics, Carbonfact can also be used to track other metrics, such as water consumption, French eco-labels and other environmental indicators — in the carbon accounting industry, they call these indicators the Product Environmental Footprint Category Rules, or PEFCR for short.

And Carbonfact has already onboarded over 150 apparel and footwear brands, including New Balance, Columbia, Carhartt and Allbirds. “We track 100% of their subsidiaries, 100% of their suppliers, 100% of their products,” Laurent said.

Each client pays tens of thousands of dollars per year to use Carbonfact. With a little back-of-the-envelope calculation, if we consider that a client pays around $20,000 per year on average, it means that the French startup already generates at least $3 million in annual recurring revenue.

It’s clear that sustainability management software is a growing segment in the world of enterprise software. But it’s also a young sector. So it’s going to be interesting to see if several industry-specific platforms can become large companies or if there will be some consolidation down the road.


Software Development in Sri Lanka

Robotic Automations

Google Gemini: Everything you need to know about the new generative AI platform | TechCrunch

April 30, 2024 5:10 AM0


Google’s trying to make waves with Gemini, its flagship suite of generative AI models, apps and services.

So what is Gemini? How can you use it? And how does it stack up to the competition?

To make it easier to keep up with the latest Gemini developments, we’ve put together this handy guide, which we’ll keep updated as new Gemini models, features and news about Google’s plans for Gemini are released.

What is Gemini?

Gemini is Google’s long-promised, next-gen GenAI model family, developed by Google’s AI research labs DeepMind and Google Research. It comes in three flavors:

  • Gemini Ultra, the most performant Gemini model.
  • Gemini Pro, a “lite” Gemini model.
  • Gemini Nano, a smaller “distilled” model that runs on mobile devices like the Pixel 8 Pro.

All Gemini models were trained to be “natively multimodal” — in other words, able to work with and use more than just words. They were pretrained and fine-tuned on a variety of audio, images and videos, a large set of codebases and text in different languages.

This sets Gemini apart from models such as Google’s own LaMDA, which was trained exclusively on text data. LaMDA can’t understand or generate anything other than text (e.g., essays, email drafts), but that isn’t the case with Gemini models.

What’s the difference between the Gemini apps and Gemini models?

Image Credits: Google

Google, proving once again that it lacks a knack for branding, didn’t make it clear from the outset that Gemini is separate and distinct from the Gemini apps on the web and mobile (formerly Bard). The Gemini apps are simply an interface through which certain Gemini models can be accessed — think of it as a client for Google’s GenAI.

Incidentally, the Gemini apps and models are also totally independent from Imagen 2, Google’s text-to-image model that’s available in some of the company’s dev tools and environments.

What can Gemini do?

Because the Gemini models are multimodal, they can in theory perform a range of multimodal tasks, from transcribing speech to captioning images and videos to generating artwork. Some of these capabilities have reached the product stage yet (more on that later), and Google’s promising all of them — and more — at some point in the not-too-distant future.

Of course, it’s a bit hard to take the company at its word.

Google seriously underdelivered with the original Bard launch. And more recently it ruffled feathers with a video purporting to show Gemini’s capabilities that turned out to have been heavily doctored and was more or less aspirational.

Google’s best Gemini demo was faked

Still, assuming Google is being more or less truthful with its claims, here’s what the different tiers of Gemini will be able to do once they reach their full potential:

Gemini Ultra

Google says that Gemini Ultra — thanks to its multimodality — can be used to help with things like physics homework, solving problems step-by-step on a worksheet and pointing out possible mistakes in already filled-in answers.

Gemini Ultra can also be applied to tasks such as identifying scientific papers relevant to a particular problem, Google says — extracting information from those papers and “updating” a chart from one by generating the formulas necessary to re-create the chart with more recent data.

Gemini Ultra technically supports image generation, as alluded to earlier. But that capability hasn’t made its way into the productized version of the model yet — perhaps because the mechanism is more complex than how apps such as ChatGPT generate images. Rather than feed prompts to an image generator (like DALL-E 3, in ChatGPT’s case), Gemini outputs images “natively,” without an intermediary step.

Gemini Ultra is available as an API through Vertex AI, Google’s fully managed AI developer platform, and AI Studio, Google’s web-based tool for app and platform developers. It also powers the Gemini apps — but not for free. Access to Gemini Ultra through what Google calls Gemini Advanced requires subscribing to the Google One AI Premium Plan, priced at $20 per month.

The AI Premium Plan also connects Gemini to your wider Google Workspace account — think emails in Gmail, documents in Docs, presentations in Sheets and Google Meet recordings. That’s useful for, say, summarizing emails or having Gemini capture notes during a video call.

Gemini Pro

Google says that Gemini Pro is an improvement over LaMDA in its reasoning, planning and understanding capabilities.

An independent study by Carnegie Mellon and BerriAI researchers found that the initial version of Gemini Pro was indeed better than OpenAI’s GPT-3.5 at handling longer and more complex reasoning chains. But the study also found that, like all large language models, this version of Gemini Pro particularly struggled with mathematics problems involving several digits, and users found examples of bad reasoning and obvious mistakes.

Early impressions of Google’s Gemini aren’t great

Google promised remedies, though — and the first arrived in the form of Gemini 1.5 Pro.

Designed to be a drop-in replacement, Gemini 1.5 Pro is improved in a number of areas compared with its predecessor, perhaps most significantly in the amount of data that it can process. Gemini 1.5 Pro can take in ~700,000 words, or ~30,000 lines of code — 35x the amount Gemini 1.0 Pro can handle. And — the model being multimodal — it’s not limited to text. Gemini 1.5 Pro can analyze up to 11 hours of audio or an hour of video in a variety of different languages, albeit slowly (e.g., searching for a scene in a one-hour video takes 30 seconds to a minute of processing).

Gemini 1.5 Pro entered public preview on Vertex AI in April.

An additional endpoint, Gemini Pro Vision, can process text and imagery — including photos and video — and output text along the lines of OpenAI’s GPT-4 with Vision model.

Using Gemini Pro in Vertex AI. Image Credits: Gemini

Within Vertex AI, developers can customize Gemini Pro to specific contexts and use cases using a fine-tuning or “grounding” process. Gemini Pro can also be connected to external, third-party APIs to perform particular actions.

Google brings Gemini Pro to Vertex AI

In AI Studio, there’s workflows for creating structured chat prompts using Gemini Pro. Developers have access to both Gemini Pro and the Gemini Pro Vision endpoints, and they can adjust the model temperature to control the output’s creative range and provide examples to give tone and style instructions — and also tune the safety settings.

Gemini Nano

Gemini Nano is a much smaller version of the Gemini Pro and Ultra models, and it’s efficient enough to run directly on (some) phones instead of sending the task to a server somewhere. So far, it powers a couple of features on the Pixel 8 Pro, Pixel 8 and Samsung Galaxy S24, including Summarize in Recorder and Smart Reply in Gboard.

The Recorder app, which lets users push a button to record and transcribe audio, includes a Gemini-powered summary of your recorded conversations, interviews, presentations and other snippets. Users get these summaries even if they don’t have a signal or Wi-Fi connection available — and in a nod to privacy, no data leaves their phone in the process.

Gemini Nano is also in Gboard, Google’s keyboard app. There, it powers a feature called Smart Reply, which helps to suggest the next thing you’ll want to say when having a conversation in a messaging app. The feature initially only works with WhatsApp but will come to more apps over time, Google says.

And in the Google Messages app on supported devices, Nano enables Magic Compose, which can craft messages in styles like “excited,” “formal” and “lyrical.”

Is Gemini better than OpenAI’s GPT-4?

Google has several times touted Gemini’s superiority on benchmarks, claiming that Gemini Ultra exceeds current state-of-the-art results on “30 of the 32 widely used academic benchmarks used in large language model research and development.” The company says that Gemini 1.5 Pro, meanwhile, is more capable at tasks like summarizing content, brainstorming and writing than Gemini Ultra in some scenarios; presumably this will change with the release of the next Ultra model.

But leaving aside the question of whether benchmarks really indicate a better model, the scores Google points to appear to be only marginally better than OpenAI’s corresponding models. And — as mentioned earlier — some early impressions haven’t been great, with users and academics pointing out that the older version of Gemini Pro tends to get basic facts wrong, struggles with translations and gives poor coding suggestions.

How much does Gemini cost?

Gemini 1.5 Pro is free to use in the Gemini apps and, for now, AI Studio and Vertex AI.

Once Gemini 1.5 Pro exits preview in Vertex, however, the model will cost $0.0025 per character while output will cost $0.00005 per character. Vertex customers pay per 1,000 characters (about 140 to 250 words) and, in the case of models like Gemini Pro Vision, per image ($0.0025).

Let’s assume a 500-word article contains 2,000 characters. Summarizing that article with Gemini 1.5 Pro would cost $5. Meanwhile, generating an article of a similar length would cost $0.1.

Ultra pricing has yet to be announced.

Where can you try Gemini?

Gemini Pro

The easiest place to experience Gemini Pro is in the Gemini apps. Pro and Ultra are answering queries in a range of languages.

Gemini Pro and Ultra are also accessible in preview in Vertex AI via an API. The API is free to use “within limits” for the time being and supports certain regions, including Europe, as well as features like chat functionality and filtering.

Elsewhere, Gemini Pro and Ultra can be found in AI Studio. Using the service, developers can iterate prompts and Gemini-based chatbots and then get API keys to use them in their apps — or export the code to a more fully featured IDE.

Code Assist (formerly Duet AI for Developers), Google’s suite of AI-powered assistance tools for code completion and generation, is using Gemini models. Developers can perform “large-scale” changes across codebases, for example updating cross-file dependencies and reviewing large chunks of code.

Google’s brought Gemini models to its dev tools for Chrome and Firebase mobile dev platform, and its database creation and management tools. And it’s launched new security products underpinned by Gemini, like Gemini in Threat Intelligence, a component of Google’s Mandiant cybersecurity platform that can analyze large portions of potentially malicious code and let users perform natural language searches for ongoing threats or indicators of compromise.

Gemini Nano

Gemini Nano is on the Pixel 8 Pro, Pixel 8 and Samsung Galaxy S24 — and will come to other devices in the future. Developers interested in incorporating the model into their Android apps can sign up for a sneak peek.

Is Gemini coming to the iPhone?

It might! Apple and Google are reportedly in talks to put Gemini to use for a number of features to be included in an upcoming iOS update later this year. Nothing’s definitive, as Apple is also reportedly in talks with OpenAI, and has been working on developing its own GenAI capabilities.

This post was originally published Feb. 16, 2024 and has since been updated to include new information about Gemini and Google’s plans for it.


Software Development in Sri Lanka

Robotic Automations

NIST launches a new platform to assess generative AI | TechCrunch

April 30, 2024 2:50 AM0


The National Institute of Standards and Technology (NIST), the U.S. Commerce Department agency that develops and tests tech for the U.S. government, corporations and the broader public, today announced the launch of NIST GenAI, a new program spearheaded by NIST to assess generative AI technologies, including text- and image-generating AI.

A platform designed to evaluate various forms of generative AI tech, NIST GenAI will release benchmarks, help create “content authenticity” detection (i.e. deepfake-checking) systems and encourage the development of software to spot the source of fake or misleading information, explains NIST on its newly-launched NIST GenAI site and in a press release.

“The NIST GenAI program will issue a series of challenge problems designed to evaluate and measure the capabilities and limitations of generative AI technologies,” the press release reads. “These evaluations will be used to identify strategies to promote information integrity and guide the safe and responsible use of digital content.”

NIST GenAI’s first project is a pilot study to build systems that can reliably tell the difference between human-created and AI-generated media, starting with text. (While many services purport to detect deepfakes, studies — and our own testing — have shown them to be unreliable, particularly when it comes to text.) NIST GenAI is inviting teams from academia, industry and research labs to submit either “generators” — AI systems to generate content — or “discriminators” — systems that try to identify AI-generated content.

Generators in the study must generate summaries provided a topic and a set of documents, while discriminators must detect if a given summary is AI-written or not. To ensure fairness, NIST GenAI will provide the data necessary to train generators and discriminators; systems trained on publicly available data won’t be accepted, including but not limited to open models like Meta’s Llama 3.

Registration for the pilot will begin May 1, with the results scheduled to be published in February 2025.

NIST GenAI’s launch — and deepfake-focused study — comes as deepfakes grow exponentially.

According to data from Clarity, a deepfake detection firm, 900% more deepfakes have been created this year compared to the same time frame last year. It’s causing alarm, understandably. A recent poll from YouGov found that 85% of Americans said they were concerned about the spread of misleading deepfakes online.

The launch of NIST GenAI is a part of NIST’s response to President Joe Biden’s executive order on AI, which laid out rules requiring greater transparency from AI companies about how their models work and established a raft of new standards, including for labeling content generated by AI.

It’s also the first AI-related announcement from NIST after the appointment of Paul Christiano, a former OpenAI researcher, to the agency’s AI Safety Institute.

Christiano was a controversial choice for his “doomerist” views; he once predicted that “there’s a 50% chance AI development could end in [humanity’s destruction]” Critics — including scientists within NIST, reportedly — fear Cristiano may encourage the AI Safety Institute to focus to “fantasy scenarios” rather than realistic, more immediate risks from AI.

NIST says that NIST GenAI will inform the AI Safety Institute’s work.


Software Development in Sri Lanka

Robotic Automations

Parloa, a conversational AI platform for customer service, raises $66M | TechCrunch

April 24, 2024 3:47 PM0


Conversational AI platform Parloa has nabbed $66 million in a Series B round of funding, a year after the German startup raised $21 million from a swathe of European investors to propel its international growth.

The company is focusing on the U.S. market in particular, where Parloa opened a New York office last year — it says this hub helped it sign up “several Fortune 200 companies” in the region. For its latest instalment, Parloa has secured Altimeter Capital as lead backer, a U.S.-based VC firm notable for its previous investments in the likes of Uber, Airbnb, Snowflake, Twilio, and HubSpot.

AI and automation in customer service is nothing new, but with a new wave of large language models (LLMs) and generative AI infrastructure, truly smart “conversational” AI (i.e. not dumb chatbots) is again firmly in investors’ focus. Established players continue to raise substantial sums, such as Kore.ai which closed a chunky $150 million round of funding a few months ago from big-name backers such as Nvidia. Elsewhere, entrepreneur and former Salesforce CEO Bret Taylor launched a new customer experience platform called Sierra, built around the concept of “AI agents,” with north of $100 million in VC backing.

Parloa is well-positioned to capitalize on the “AI with everything” hype that has hit fever pitch these past couple of years, as companies seek new ways to improve efficiency through automation.

Founded out of Germany in 2018, Parloa has already secured high-profile customers such as European insurance giant Swiss Life and sporting goods retailer Decathlon, which use the Parloa platform to automate customer communications including emails and instant messaging.

However, “voice” is where co-founder and CEO Malte Kosub reckons Parloa stands out.

“Our strategy has always been centered around ‘voice first,’ the most critical and impactful facet of the customer experience,” Kosub told TechCrunch over email. “As a result, Parloa’s AI-based voice conversations sound more human than any other solution.”

Parloa platform Image Credits: Parloa

Co-founder and CTO Stefan Ostwald says that AI has been a core part of Parloa’s DNA since its inception six years ago, using a mix of proprietary and open source LLMs to train models for speech-to-text use-cases.

“We’ve trained a variety of speech-to-text models on phone audio quality and customer service use cases, developed a custom telephony infrastructure to minimize latency — a key challenge in voice automation — and a proprietary LLM agent framework for customer service,” he said.

Prior to now, Parloa had raised around $25 million, the bulk of which arrived via its Series A round last year. And with another $66 million in the bank, it’s well-financed to double down on both its European and U.S. growth, with Kosub noting that it has tripled its revenue in each of the past three years.

“We successfully entered the U.S. market in 2023 — we’ve always had confidence in the excellence and competitiveness of our product, however the overwhelming and rapid success it achieved in the U.S. surpassed everyone’s expectations,” Kosub said.

Aside form lead investor Altimeter, Parloa’s Series B round included cash injections from EQT Ventures, Newion, Senovo, Mosaic Ventures and La Familia Growth. Today’s funding brings Parloa’s total capital raised to-date to $98 million, following its $21 million Series A funding round led by EQT Ventures in 2023.


Software Development in Sri Lanka

Robotic Automations

Google-backed Glance pilots Android lockscreen platform in US | TechCrunch

April 24, 2024 9:06 AM0


Glance, which operates a lockscreen platform targetting Android smartphones, is setting its sights on the U.S. market. The Indian startup recently commenced a pilot program in partnership with Motorola and Verizon in the U.S., with plans for a full launch in the country later this year, sources familiar with the matter told TechCrunch.

The Bengaluru-headquartered startup, backed by investors including Google and Jio Platforms, has already made significant inroads in India, Southeast Asia, and Japan, where it expanded last year. Glance’s technology delivers a customized feed of news, local events, sports updates, media content as well as interactive games directly to users’ lockscreens without requiring them to install additional apps.

Android smartphone manufacturers have faced increasing pressure to boost revenue in recent years amid fierce competition and slim profit margins on hardware. Initially, many of these companies sought out new revenue streams to supplement their core business. However, as Glance’s lockscreen platform gained traction, coupled with its privacy stance, a growing number of smartphone makers have acknowledged its potential as a powerful tool for differentiation, industry executives say.

Glance doesn’t collect personal data of users, instead relying on usage pattern to inform its recommendation engine. It’s also working with Qualcomm to build a unique AI-powered lockscreen experience, according to one source. That partnership, if it materializes, will also allow Glance to significantly reduce the data it consumes for its personalized feed and also move much of the processing to on-device.

In the U.S., Glance doesn’t plan to display ads on the lockscreen, according to one of the sources. Glance ships pre-installed on the device, but can be easily removed.

Lockscreen and other non-app screens are becoming crucial real-estates for smartphone vendors and brands. “‘Surfaces’ exist even today, driven by 3 types of players — OEM-driven, OS-driven, and surface-first innovation driven,” BCG wrote in a recent industry report. “Players like Glance are the most interesting of the lot w.r.t. innovation in AI deployed, to serve relevant content for a user every single time.”

Glance’s lockscreen platform today reaches more than 450 million smartphones and is active on about 300 million of them, according to a person familiar with the matter.

In the U.S., the eponymous startup plans to tie-up with more telecom operators as well as brands including CNN and the NBA, sources said, requesting anonymity as the details are private. The recently launched Moto G Power smartphone in the U.S. shipped with Glance’s platform. A Glance spokesperson declined to comment.

Glance has been eyeing to launch in the U.S. for at least two years, TechCrunch earlier reported. It’s not clear why it didn’t launch in the U.S. sooner.

The Indian startup’s lockscreen technology has already proven successful in driving user engagement and app installations for brand partners. A nine-week partnership with Indian streaming service JioCinema last year resulted in 9 million incremental app installs from over 100 million unique impressions, BCG wrote. The campaign also targeted dormant users, leading to a 12.5% increase in app opens and converting the install base into daily active users, the report added.


Software Development in Sri Lanka

Robotic Automations

EXCLUSIVE: Perplexity is raising $250M+ at a $2.5-$3B valuation for its AI search platform, sources say

April 23, 2024 8:59 PM0


Perplexity, the AI search engine startup, is a hot property at the moment. TechCrunch has learned that the company is currently raising at least $250 million more at a valuation of between $2.5 billion and $3 billion.

The news comes on the heels of two other big fundraises that have seen company’s valuation leapfrog in the last four months: in January the company raised nearly $74 million at a valuation of $540 million (up from $121 million in April 2023). And at the beginning of March, the company closed $56 million on a valuation of $1 billion — a raise that has been quietly public since then (it was on PitchBook’s database for one), and which Bloomberg highlighted earlier today.

Those two reported rounds are not the full story. We understand from multiple sources close to the company that it is actually also raising a further round to capitalize on the attention it’s getting in the market. NEA and IVP, both previous backers of the company, are among those looking to invest in this larger round, according to sources.

Whether they or other previous backers participate, a source said, may depend on how willing Perplexity is to work with existing investors rather than diversity, expanding its cap table to bring in new investors.

“They are growing very rapidly,” a partner from an existing investor said. “Yes we will look to participate.”

The core of Perplexity’s product is a generative AI-based search engine that provides results using a chatbot-style interface. It’s definitely not the only company in generative AI pursuing the search opportunity: that is essentially how many people are using products like ChatGPT and Microsoft’s Bing (powered by OpenAI), and Google is making a big push to improve search results with its Gemini LLM.

But Perplexity is building its algorithms incorporating a variety of LLMs, the idea being that this produces a more accurate and richer response.

“Unlike other enterprise tools for knowledge work like Microsoft Copilot, Perplexity Enterprise Pro is also the only enterprise AI offering that offers all the cutting-edge foundation models in the market in one single product: OpenAI GPT-4, Anthropic Claude Opus, Mistral, and more to come,” CEO and co-founder Aravind Srinivas noted earlier today. “This gives customers and users choices to explore and customize their experience depending on their use cases.” That “more to come” may well be including more from Hugging Face and Meta, if Srinivas’s public endorsements and investor lists are anything to go by.

Considering that the company has only been around since 2022, Perplexity’s current investor list is already long, running to 46 names according to PitchBook data.

In addition to IVP and NEA, it includes other notable VCs such as Sequoia, Bessemer and Kindred; strategic backers like Nvidia, Databricks and Bezos Expeditions; and many recognizable individuals such as Jeff Bezos, Meta’s chief AI scientist Yann LeCun, Naval Ravikant, Susan Wojcicki, Elad Gil, Nat Friedman, and Clément Delangue from Hugging Face. A newer backer, Daniel Gross, led the $56 million round from March with other new backers Stanley Druckenmiller, Y Combinator head Garry Tan and Figma’s CEO Dylan Field also participating, among others.

One fundraise coming rapidly on the heels of another is reminiscent of rolling fundraising that we’ve seen from other big startups over the years. In the years leading up to is IPO during a time of rapid growth and major attention, Snap regularly appeared to be raising money on an ongoing basis. These days, it appears to be all about AI, with companies like OpenAI, Anthropic and Mistral all raising at a rapid pace and seeing their valuations skyrocket along with that.

In the case of Perplexity, the startup is standing out in the market for a couple of reasons. Most obviously, it’s one of the ambitious, albeit smaller, hopefuls in the race to build generative AI services. Its unique position in the market is that it’s not focused on the race to build multi-purpose large language models. Instead, taking a page from one of the biggest technology companies in the world today, it is tacking one specific product, at least for now: search.

Perplexity is not the only startup in AI that is building on very focused opportunities and by targeting enterprise. Synthesia in the UK is taking a similar approach with AI video tools, aiming them specifically at the business market, for the building of training and customer support video content.

In the case of Perplexity, the startup offers its tools on free and enterprise, paid tiers, and so far its processed 75 million queries this year and is currently on ARR of $20 million, according to Bloomberg.

Its reason for raising again so soon? Yes, perhaps to capitalize on customer and investor interest at what one investor described as a “zeitgeist moment” for the startup. But also because of the mechanics of building any kind of AI service right now.

“Compute is very expensive, so they may need to raise” for that reason alone, one said.

We have reached out to Srivinivas for comment and will update this post as we learn more.




Software Development in Sri Lanka

Robotic Automations

Texture makes a bid to become the world’s go-to platform of the energy transition | TechCrunch

April 23, 2024 6:48 PM0


Platform is a word that gets tossed around a lot in technology circles, so much so that it’s often misused. But here’s the basic business school definition: a platform is a company or business model that creates more value for participants than it captures for itself.

Consider that some of the most successful companies in tech have helped other businesses make more money in aggregate than they make for themselves. A couple decades ago, Microsoft made lots of money facilitating the PC revolution. More recently, Apple said that developers which used its App Store generated $1.1 trillion in sales in 2022, nearly triple what the company made itself that year.

Serial startup veteran Sanjiv Sanghavi, who has logged experience as the co-founder of ClassPass and chief product officer at Arcadia, thinks it’s high time the energy transition birthed its equivalent. In fact, he spent years as a venture partner at Day One Ventures looking in vain to invest in such a company. “So I decided to go and build it,” he told TechCrunch.

Sanghavi’s newest company, Texture, seeks to become a common data collection and sharing platform for renewable power sources like wind, solar, and batteries. “We’ve done a really exceptional job of distributing hardware over the energy grid in the last decade. Making solar affordable, making batteries affordable, getting EVs out there,” he said. Each solar array or battery installation doesn’t have the power to bring clean, affordable power to the grid on its own. In aggregate, though, they have a much better chance at displacing fossil fuels.

But many of those systems come from different manufacturers, making basic communication between them challenging, let alone anything that looks like interoperability. “If there’s a lack of standards, there’s a lot of walled gardens being built,” Sanghavi said. “Our view is that Texture can provide the technology stack that should accelerate everybody on top of it.”

The company is incorporating data directly from the equipment itself. When manufacturers have APIs available, it connects with those directly, similar to how Plaid connects with banks. For those that don’t, it will work to build the necessary software to make the connections possible. Battery manufacturers, for example, may not prefer to maintain an API themselves since it’s not one of their core competencies.

In other cases, where a solution already exists, it works with a third party. “One of the tenets of Texture really is not to rebuild everything. There are companies out there that are tracking electricity usage, grid status, and their meter data, tariff data,” Sanghavi said. “Why don’t we work together?”

On the other end of the equation, target customers for Texture’s product include installers, who might sell monitoring and maintenance plans, and virtual power plant operators, who would benefit from being able to include batteries from a range of manufacturers. By having more data, each of these would be able to sell more of their product. Texture charges customers by how many megawatts they have under management.

Amperesand raises $12.5M seed round to remake the humble 140-year-old transformer

The company recently raised a $7.5 million seed round from Abstract Ventures, Day One Ventures, Equal Ventures, Lerer Hippeau, and a handful of angels, including Kiran Bhatraju, CEO of Arcadia. It plans to use this money to further develop and test the product with the first set of customers.

Not every supplier has opened their products to Texture yet, but Sanghavi is obviously hoping they will. Sure, they could charge for API access now, he said, but he thinks Texture’s pitch to them will resonate: “If you play as part of the ecosystem, you expand the market an exponential amount of times. Even if your market share remains the same, your business becomes five times bigger.” If Texture succeeds in deriving on that promise to customers, then it will truly be a platform for the energy transition.


Software Development in Sri Lanka

Robotic Automations

Two widow founders launch DayNew, a social platform for people dealing with grief and trauma | TechCrunch

April 23, 2024 5:33 PM0


After losing their husbands in devastating and unexpected ways, Karine Nissim and Eloise Bune D’Agostino discovered there were no suitable places where people could go to face all the challenges that surface during the grieving process, including daunting tasks such as organizing a funeral ceremony and donating belongings, as well as scouring the internet for support groups.

Being seasoned entrepreneurs themselves—Nissim having sold her startup DogVacay to Rover in 2017 and Bune D’Agostino, who co-founded Tentrr and Handwriting.io—the two widow founders decided to take matters into their own hands and build what they call a “360 healing” platform that provides a range of services and resources to help with grief and other hardships like divorce, illness, and trauma.

Now available on the App Store, Google Play Store, and the web, DayNew is a new grief support platform, social community, educational hub, and task manager app wrapped up into one, user-friendly package. At its core, DayNew aims to be a safe space for users to connect with others, share their stories, and receive support from the community.

“From hospice centers to bereavement groups to online therapy, regular therapists and psychiatrists, to funeral homes to all of the other services, there was not one place that we could go that could hold the whole journey for us,” Nissim told TechCrunch. “So, we set out to create a customized roadmap that is really highly tailored to each person based on their trauma type… When you come to DayNew, we are ready to meet you with organizational, emotional, and social support.”

Some people find it hard to ask for help because they don’t want to feel like a burden to their family and friends. DayNew’s Community feed acts as a dedicated space for users to be direct about what they want from supporters, whether it be money to buy groceries, a place to sell and donate belongings, or a job listing for a babysitter.

“[Eloise and I] got lots of flowers and casseroles. While that’s beautiful, generous and thoughtful, we also got a lot of comments like ‘Whatever you need,’ and we were always ill-equipped on how to answer that or didn’t feel comfortable… The community page takes the ickiness of the ask out. It also takes the ickiness out of the supporters’ side because now they actually know what you need, and they don’t feel like they’re bothering you.” Nissim said.

There’s also a “Find a Buddy” feature for users to get one-on-one support from people who are going through similar tragedies. Users can search for others with the same hashtags in their profiles, including #partnerloss, #parentloss, #cancerloss, #covidloss, and so on.

Similar to other grief support platforms (Grief Refuge, Untangle, and Grief Works), DayNew has a Journal feature where users can vocalize how they feel by either answering prompts or freehanding an entry that speaks from the heart. The company compares the prompts to homework from a therapist, asking tough and thought-provoking questions such as “What’s something about grief you never knew before?” and “What’s something you wish you could tell your younger self?” Depending on comfort level, the journal entry can be kept private or shared publicly on the Community feed.

Additionally, there’s a daily mood tracker component for users to check in with themselves and log their moods on a scale of 1 to 10.

Image Credits: DayNew

DayNew offers various other features to assist users throughout their journey, including personalized lists for users to check off overwhelming tasks (sell assets, get life insurance, apply for widow social security benefits, and so on) at their own pace, a ChatGPT-powered AI tool that provides emotional advice, and a “Learn & Grow” page with educational and motivational content.

Nissim explained that the platform is also launching virtual workshops and in-person events to bring people together and teach them the benefits of “grounding and meditation” in order to promote healing. The online classes cost around $36 and feature special guests like experts, scientists, and psychologists. The first session is on May 21 and will be hosted by the founders themselves. In mid-July, there will be an in-person retreat in Mexico for about $1,800.

In the next iteration of the platform, DayNew plans to introduce a gifting feature where friends and family members can purchase classes to give to a loved one.

DayNew is free to join but it also offers a $5 per month subscription for users who want to access premium features, including the “Find a Buddy” service, direct messages, and being able to comment on public community posts.

In the digital age, users are embracing grief-related products and services to cope with death. What once was considered a taboo topic, grievers can now openly discuss loss and be reassured that they’re not alone. However, it’s important to realize that these services shouldn’t replace proper therapy and counseling but should act as an additional outlet to express their feelings.

Empathy closes $47M for AI to help with the practical and emotional bereavement process

Lalo launches an app to memorialize loved ones


Software Development in Sri Lanka

Robotic Automations

Equities platform Midas raises $45M Series A as fintech retains its sparkle in Turkey | TechCrunch

April 19, 2024 10:35 PM0


Midas, a fintech startup that allows people in Turkey to invest in U.S. and Turkish equities, says it has raised $45 million in a funding round led by Portage Ventures of Canada.

The startup is aimed at Turkey’s retail investor market and claims to have more than 2 million users. Its pitch is that it charges significantly lower transaction and commission fees for Turkish customers who want to invest in U.S. or Turkish stocks. It also offers financial content, real-time stock market data and news, and company profiles — all to educate what many consider to be somewhat of an emerging market.

“If you came to Turkey three years ago, there were only 1.5 million investors. That’s in a country of 80 million,” Egem Eraslan, CEO and founder of Midas, told TechCrunch. “Capital markets penetration rates were very, very low. Mobile banking in Turkey is very good and widespread, but there was a lack of investment in equities products because of a lack of infrastructure.”

According to Eraslan, Midas managed to change that dynamic by building its own infrastructure and providing a decent user experience. “We were extremely capital-efficient. We built much of the initial infrastructure product and licensing with less than $500,000, and that allowed us to launch, get traction, raise capital and break that deadlock. We might be the only new broker in the world that launched self-clearing, self-custody, and self-execution.”

Midas is not dissimilar to U.S.-based Robinhood, which has become a giant in the space by providing retail investors an easy avenue to investing in the financial markets. But Eraslan explains that his company has had take a different tack in Turkey.

“We had to launch multiple products with our own self-clearing, custody, and with the entire value chain. If you’re Robinhood, you don’t have to do self-custody or self-clearing.”

Midas now plans to use the new funding to roll out three new products: cryptocurrency trading, mutual funds, and savings accounts. The company has plans to expand beyond Turkey, and aims to target countries in the MENA region.

International Finance Corporation, Spark Capital, Earlybird Digital East Fund, and Revo Capital also participated in the round. The company last raised an $11 million seed round in 2022. Arriving within three years of its founding, Midas’ latest fundraise is one of the largest by a Turkish fintech in recent years, close behind embedded finance startup Param, which raised $50 million in 2022.

Cem Sertoglu, managing partner of Earlybird Digital East Fund, of the startup’s early investors said, “Having timed the explosion in demand in the Turkish investment market perfectly as the first digital-native investment platform, Midas has been executing flawlessly. Winning the domestic market in the world’s 11th-largest economy will already be a success for Midas, but its ambitions lie further than that.”

In a statement, Paul Desmarais III, co-Founder of Portage, and CEO and chairman of Sagard, said: “Midas is leading a wave of transformation within Turkey’s financial landscape. Globally, Portage invests in transformational financial technology and Midas is poised to lead that initiative in a region of early adopters.”


Software Development in Sri Lanka

Robotic Automations

Exclusive: Checkr, the background-screening platform last valued at $5 billion, cuts 32% of workforce

April 19, 2024 4:09 PM0


Checkr, a 10-year-old startup that offers employee background checks and was last valued at $5 billion in April 2022, has laid off 382 employees as companies are not significantly hiring talent.

TechCrunch exclusively learned that Checkr conducted the layoffs across all departments and different levels on Tuesday. The San Francisco–based startup confirmed the layoffs in an email.

“In response to economic conditions that have impacted companies’ hiring, we made the difficult and painful decision to reduce the size of our team. This will allow us to operate more efficiently and ensure the long-term health of our business,” a Checkr spokesperson said in the statement.

The job cuts — which affected 32% of the company’s workforce — came nearly two years after Checkr announced the acquisition of Inflection, the startup behind GoodHire, a background-checking platform for small- and midsized businesses. At the time, The Wall Street Journal reported the deal was worth $400 million.

Backed by storied investors, including Durable Capital Partners, Fidelity Management & Research, Franklin Templeton, BOND and Coatue Management, Checkr lets companies do background checks by looking into driving and criminal records and basic identity confirmation of their potential employees. The startup offers an online form to let companies run those checks or use its API, which can be integrated within their hiring systems or onboarding software, including Workable and Zenefits.

A comprehensive list of 2023 & 2024 tech layoffs

Founded in 2014, Checkr counts Uber, Instacart, Netflix, Adecco, Airbnb and Coinbase among its key customers. Its customer base grew to more than tens of thousands of companies ranging from small and medium businesses to Fortune 500 employers in 2022. Initially, the startup was limited to Silicon Valley, but it expanded its presence beyond the Valley in 2016.

Checkr has given the affected employees a minimum of 10 weeks of severance and health insurance, as well as career and mental health support, the spokesperson said.

The startup did not answer questions about its runway and fundraising plans. To date, it has raised $679 million, with the last round of $250 million announced in September 2021.


Software Development in Sri Lanka

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