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Artificial Intelligence

Armenia’s 10web brings AI website-building to WordPress


Generative AI has done an impressive job in improving productivity in a wide range of areas, including website building. There’s no lack of tools that now allow one to generate web designs by simply describing what they want in prompts, including established player Wix and bootstrapped startups like Relume. 10web, a company based out of Armenia, is entering the race and believes it has an edge.

10web allows users to quickly generate websites built with WordPress, the widely-used content management system that is notoriously hard to use for beginners, using text prompts. Unlike Wix and Squarespace, WordPress is open-source, meaning many features don’t come out of the box and require more advanced web design skills; it doesn’t come with hosting services either, so users have to manage more backend tasks.

WordPress still powers around 40% of all the websites on the internet, thanks to its customization options, according to estimates by w3techs. Shopify followed in second place amid a boom of direct-to-consumer ecommerce as vendors look to build their online stores with the help of the Canadian company rather than relying on Amazon.

To make WordPress more intuitive to use, 10web’s Yerevan-based engineering team has integrated generative AI models like Llama 2, GPT-4, and Stable Diffusion into its site-building platform. Such a tool requires a great deal of development effort because “architecturally, building a platform for WordPress is not easy,” said 10web’s co-founder Arto Minasyan, who also runs Krisp, a startup that removes background noise from audio using machine learning.

“You need to have a very good hosting infrastructure. You need to have a managed service to support WordPress security, backups and uptime. All those things are very, very hard because each of the websites is basically an instance,” he added. “In contrast, if you are building on a closed source solution, let’s say Wix or Squarespace, you just build one backend, and then for each website, you just generate some pages.”

Minasyan is confident that focusing on solving WordPress’s usability will pay off eventually because of the sheer size of its open-source community: two million developers. Founded in 2017, 10web currently operates with a positive cash flow. Around 20,000 of its users are paying customers (some SMB customers might have several hundred websites, Minasyan noted). Altogether, 1.5 million sites have been generated with 10web.

10web has two ways to monetize — charging fees per website or by traffic. It has plans to add a payment system, which will allow users to charge their customers and 10web to take a cut of the charge as commission fees.

The company is generating $5 million in annual recurring revenue at the moment and is expected to reach $25 million in ARR by the end of next year, Minasyan said. The founder attributed the company’s growth partly to its favorable location in Armenia. Like other former members of the Soviet Union, Armenia enjoys abundant affordable engineering talent.

“We have AI talent, which is probably four times cheaper in Armenia than in the U.S. And here, we can access the best AI talent possible,” the founder suggested. “But if you are a web builder based in California, you gotta compete with Google, Amazon and OpenAI, so it’s not easy to get the best talent.”

Armenia’s budding tech hub in its capital city has spawned the country’s first unicorn, Picsart, which provides a playbook for fellow startups to follow. Given Armenia’s relatively small economy, its entrepreneurs have historically ventured overseas, particularly targeting the U.S. They employ engineers in Armenia to take advantage of the tech talent at home while hiring marketing and business development headcounts in the U.S., a strategy also shared by 10web’s 70-person strong staff. And of course, having a footprint in the U.S. can be advantageous to fundraising.

“99% of Armenian startups target the U.S. market,” said the founder. “If you want to raise less than $1 million, you can raise from Armenian VCs, but if you want to raise a couple million for seed or tens of millions for Series A, you need to go to the U.S.”



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by Team SNFYI

Facebook is testing a new feature that invites some users—mainly in the US and Canada—to let Meta AI access parts of their phone’s camera roll. This opt-in “cloud processing” option uploads recent photos and videos to Meta’s servers so the AI can offer personalized suggestions, such as creating collages, highlight reels, or themed memories like birthdays and graduations. It can also generate AI-based edits or restyles of those images. Meta says this is optional and assures users that the uploaded media won’t be used for advertising. However, to enable this, people must agree to let Meta analyze faces, objects, and metadata like time and location. Currently, the company claims these photos won’t be used to train its AI models—but they haven’t completely ruled that out for the future. Typically, only the last 30 days of photos get uploaded, though special or older images might stay on Meta’s servers longer for specific features. Users have the option to disable the feature anytime, which prompts Meta to delete the stored media after 30 days. Privacy experts are concerned that this expands Meta’s reach into private, unpublished images and could eventually feed future AI training. Unlike Google Photos, which explicitly states that user photos won’t train its AI, Meta hasn’t made that commitment yet. For now, this is still a test run for a limited group of people, but it highlights the tension between AI-powered personalization and the need to protect personal data.

by Team SNFYI

News Update Bymridul     |    March 14, 2024 Meesho, an online shopping platform based in Bengaluru, has announced its largest Employee Stock Ownership Plan (ESOP) buyback pool to date, totaling Rs 200 crore. This buyback initiative extends to both current and former employees, providing wealth creation opportunities for approximately 1,700 individuals. Ashish Kumar Singh, Meesho’s Chief Human Resources Officer, emphasized the company’s commitment to rewarding its teams, stating, “At Meesho, our employees are the driving force behind our success.” Singh further highlighted the company’s dedication to providing opportunities for wealth creation despite prevailing macroeconomic conditions. This marks the fourth wealth generation opportunity at Meesho, with the size of the buyback program increasing each year. In previous years, Meesho conducted buybacks worth over Rs 8.2 crore in February 2020, Rs 41.4 crore in November 2020, and Rs 45.5 crore in October 2021. Meesho’s profitability journey began in July 2023, making it the first horizontal Indian e-commerce company to achieve profitability. Despite turning profitable, Meesho continues to maintain positive cash flow and focuses on enhancing efficiencies across various cost items. The company’s revenue from operations for FY 2022-23 witnessed a remarkable growth of 77% over the previous year, amounting to Rs 5,735 crore. This growth can be attributed to Meesho’s leadership position as the most downloaded shopping app in India in both 2022 and 2023, increased transaction frequency among existing customers, and a diversified category mix. Additionally, Meesho’s focus on improving monetization through value-added seller services contributed to its revenue growth. Meesho also disclosed its audited performance for the first half of FY 2023-24, reporting consolidated revenues from operations of Rs 3,521 crore, marking a 37% year-over-year increase. The company achieved profitability in Q2 FY24, with a significant reduction in losses compared to the previous year. Furthermore, Meesho recorded impressive app download numbers, reaching 145 million downloads in India in 2023 and surpassing 500 million downloads in H1 FY 2023-24. Follow Startup Story Source link

by Team SNFYI

You might’ve heard of Grok, X’s answer to OpenAI’s ChatGPT. It’s a chatbot, and, in that sense, behaves as as you’d expect — answering questions about current events, pop culture and so on. But unlike other chatbots, Grok has “a bit of wit,” as X owner Elon Musk puts it, and “a rebellious streak.” Long story short, Grok is willing to speak to topics that are usually off limits to other chatbots, like polarizing political theories and conspiracies. And it’ll use less-than-polite language while doing so — for example, responding to the question “When is it appropriate to listen to Christmas music?” with “Whenever the hell you want.” But Grok’s ostensible biggest selling point is its ability to access real-time X data — an ability no other chatbots have, thanks to X’s decision to gatekeep that data. Ask it “What’s happening in AI today?” and Grok will piece together a response from very recent headlines, while ChatGPT, by contrast, will provide only vague answers that reflect the limits of its training data (and filters on its web access). Earlier this week, Musk pledged that he would open source Grok, without revealing precisely what that meant. So, you’re probably wondering: How does Grok work? What can it do? And how can I access it? You’ve come to the right place. We’ve put together this handy guide to help explain all things Grok. We’ll keep it up to date as Grok changes and evolves. How does Grok work? Grok is the invention of xAI, Elon Musk’s AI startup — a startup reportedly in the process of raising billions in venture capital. (Developing AI’s expensive.) Underpinning Grok is a generative AI model called Grok-1, developed over the course of months on a cluster of “tens of thousands” of GPUs (according to an xAI blog post). To train it, xAI sourced data both from the web (dated up to Q3 2023) and feedback from human assistants that xAI refers to as “AI tutors.” On popular benchmarks, Grok-1 is about as capable as Meta’s open source Llama 2 chatbot model and surpasses OpenAI’s GPT-3.5, xAI claims. Image Credits: xAI Human-guided feedback, or reinforcement learning from human feedback (RLHF), is the way most AI-powered chatbots are fine-tuned these days. RLHF involves training a generative model, then gathering additional information to train a “reward” model and fine-tuning the generative model with the reward model via reinforcement learning. RLHF is quite good at “teaching” models to follow instructions — but not perfect. Like other models, Grok is prone to hallucinating, sometimes offering misinformation and false timelines when asked about news. And these can be severe — like wrongly claiming that the Israel–Palestine conflict reached a ceasefire when it hadn’t. For questions that stretch beyond its knowledge base, Grok leverages “real-time access” to info on X (and from Tesla, according to Bloomberg). And, similar to ChatGPT, the model has internet browsing capabilities, enabling it to search the web for up-to-date information about topics. Musk has promised improvements with the …