NEWS

Snap acquires Fit Analytics, a fitting technology startup, to double down on fashion and e-commerce

Published

4 years ago

March 17, 2021

Snap acquires Fit Analytics, a fitting technology startup, to double down on fashion and e-commerce

“Snap, Inc. is a camera company,” Snap notes on its homepage, and while a lot of its effort up to now have been about using that camera ethos to help people share images of their lives with their social circles on its flagship app Snapchat, today the company made an acquisition to further that camera reach in another direction: selling fashion and more generally, e-commerce and shopping.

Snap today confirmed that it has acquired Fit Analytics, a startup based in Berlin that has built technology to help shoppers find the right-sized apparel and footwear from online retailers, along with a wider set of personalization tools and other analytics to help retailers figure out how to sell more overall.

Fit Analytics already works with a number of big retailers, including North Face, Asos, Calvin Klein, Patagonia, Puma, and many more — in all, some 18,000 retailers already.

In other words, Snap is adding not just a technology team — there are 100 staff at the company, based in Berlin, who will be reporting to Snap VP of Engineering Nima Khajehnouri — but a substantial e-commerce technology business into its portfolio.

Fit Analytics has confirmed that it will be continuing to operate its existing business, while also working on helping Snap build out its shopping platform.

“If you are a Fit Analytics partner, this is only the beginning,” Fit Analytics’ CEO and co-founder Sebastian Schulze wrote in a blog post announcing the deal. “By leveraging Snap’s scale and capabilities, we will not only continue to service our existing clients, but also deepen our relationships and offerings with our brand partners and retailers. Our main focus going forward will be to scale the Fit Analytics business and work with Snap to grow their shopping platform, leveraging our technology and expertise. Our teams will be jointly executing on next-gen shopping, fashion and style offerings.”

Fit Analytics’ technology lets people enter their own measurements into a tool that uses machine learning to match those dimensions up to the clothes or shoes in question to find the best fit.

Notably, although it is not the focus for the company right now, Fit Analytics also has built technology to match clothing using images that customers upload themselves — an interesting area considering Snap’s focus on the visual experience, on visuals created by its users — and of course the features it has built around lenses and other augmented reality experiences to let people play with different versions of themselves and how they look.

fitfinder

The terms of the deal are not being disclosed. Fit Analytics, which used to be called UpCload (and actually launched back in 2011 at a TC Disrupt event in Beijing focused mainly on “webcam” technology — this was the days before smartphone-created selfies were de rigueur) had disclosed less than $1 million in funding according to PitchBook data, although that list of customers implies that it was generating strong revenues.

Social shopping spree

Snap’s acquisition of Fit Analytics pulls on a few different strategic threads for the social media company.

For starters, it will give Snap another way to diversify its revenues. The company is now making nearly $1 billion a quarter in revenues (in its Q4 earnings, it posted sales of $911 million). The majority of that is coming from advertising on Snapchat, so Snap is naturally looking for other ways of making money.

Whether Fit Analytics is integrated into Snapchat or not, and regardless of what will happen with how Apple and Google let apps monetize on their mobile platforms, Fit Analytics is already likely pulling in a substantial amount of revenue by way of its e-commerce services for retailers.

Covid-19 has led a lot of retailers to rethink how well their e-commerce experiences work, and that could have meant more activity for companies like Fit Analytics. All that will now be funneled on to Snap’s balance sheet.

Its advertising business, meanwhile, reveals that Snap already has a substantial relationship with fashion and beauty brands.

In those Q4 earnings alone, it noted augmented reality campaigns with NYX Professional Makeup and Ralph Lauren, as well as a partnership with Perfect Corp for 200 beauty brands to upload catalogs to the Snap Camera for augmented reality try-on. Fit Analytics will help it deepen those engagements, by giving Snap another range of features that it can build out for those customers. Come for the AR filter to see how you look in a Ralph Lauren sweater, and then…shop the look.

In addition to diversifying its revenues, it could be a sign of how Snap is diversifying the kinds of bells and whistles it’s providing for its audience. Again, Snap is not commenting on how and when it plans to integrate Fit Analytics’ tools, but it is notable that Snapchat’s core audience of teen and younger users also happens to be a major target for fashion retailers, too.

Clothing, fashion accessories and shoes together made up some 33% of US teenagers’ spend in Fall 2020, according to research from Piper Sandler, against other categories like video games, music, and food. (Books got a paltry 1% – I guess they didn’t survey many bookish types…)

Slicing up the pie somewhat differently, Piper Sandler said that the majority of spend, 40%, was dedicated to “How I Look (aka the Selfie Budget)” — putting what Fit Analytics enables more squarely in the same categories that Snap is also looking to address.

Sidenote: Piper Sander’s research shows that Amazon is far and away the biggest destination for fashion shopping right now for teens, which shows how fragmented the D2C market is.

That also sets up an interesting opportunity for Snap, by way of Snapchat, to provide another shopping channel for those D2C brands, while also riding on the coattails, so to speak, of Instagram and its growing role in the world of social media-based commerce.

At its core, Fit Analytics’ tools are part of what you might think of as the “missing link” in fashion e-commerce.

The benefits of online commerce are pretty extensive: people can shop whenever they want; they can get a much bigger selection of items, since the retail “space” is limited only by the time shoppers want to commit to shopping; they can get more personalised experiences; and they are increasingly getting a diversified range of delivery options and times.

The biggest drawback has, of course, been in the lack of “hands-on” interaction.

Put more simply, you have no way of trying on clothes and shoes, leading to the other big pain point: returns. Fit Analytics is part of the army of startups that have been building technology to fill that gap: others have included companies that provide visualizations of how clothes can look on a person.

Notably, these are areas where Amazon has also been making significant investments — in addition to making acquisitions like the 3D modeling startup Body Labs, it has launched a plethora of services to make it easier for people to buy from it, such as its try-on-and-return feature Prime Wardrobe. The e-commerce giant has a lot of weapons in its arsenal, but technology undoubtedly has been helping it win the fashion commerce race.

Snap has made about 20 acquisitions to date, covering areas like advertising technology, location-based services, services to further the company’s AI and augmented reality products, and forays into music. Fit Analytics appears to be the first focused on shopping and e-commerce, and specifically fashion, but if its interest in shopping continues to grow, I wouldn’t be surprised if it’s the last.

TechCrunch

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NEWS

OpenAI Introduces Fine-Tuning for GPT-4 and Enabling Customized AI Models

Published

2 months ago

August 21, 2024

Max

OpenAI Introduces Fine-Tuning for GPT-4 and Enabling Customized AI Models

OpenAI has today announced the release of fine-tuning capabilities for its flagship GPT-4 large language model, marking a significant milestone in the AI landscape. This new functionality empowers developers to create tailored versions of GPT-4 to suit specialized use cases, enhancing the model’s utility across various industries.

Fine-tuning has long been a desired feature for developers who require more control over AI behavior, and with this update, OpenAI delivers on that demand. The ability to fine-tune GPT-4 allows businesses and developers to refine the model’s responses to better align with specific requirements, whether for customer service, content generation, technical support, or other unique applications.

Why Fine-Tuning Matters

GPT-4 is a very flexible model that can handle many different tasks. However, some businesses and developers need more specialized AI that matches their specific language, style, and needs. Fine-tuning helps with this by letting them adjust GPT-4 using custom data. For example, companies can train a fine-tuned model to keep a consistent brand tone or focus on industry-specific language.

Fine-tuning also offers improvements in areas like response accuracy and context comprehension. For use cases where nuanced understanding or specialized knowledge is crucial, this can be a game-changer. Models can be taught to better grasp intricate details, improving their effectiveness in sectors such as legal analysis, medical advice, or technical writing.

Key Features of GPT-4 Fine-Tuning

The fine-tuning process leverages OpenAI’s established tools, but now it is optimized for GPT-4’s advanced architecture. Notable features include:

Enhanced Customization: Developers can precisely influence the model’s behavior and knowledge base.
Consistency in Output: Fine-tuned models can be made to maintain consistent formatting, tone, or responses, essential for professional applications.
Higher Efficiency: Compared to training models from scratch, fine-tuning GPT-4 allows organizations to deploy sophisticated AI with reduced time and computational cost.

Additionally, OpenAI has emphasized ease of use with this feature. The fine-tuning workflow is designed to be accessible even to teams with limited AI experience, reducing barriers to customization. For more advanced users, OpenAI provides granular control options to achieve highly specialized outputs.

Implications for the Future

The launch of fine-tuning capabilities for GPT-4 signals a broader shift toward more user-centric AI development. As businesses increasingly adopt AI, the demand for models that can cater to specific business needs, without compromising on performance, will continue to grow. OpenAI’s move positions GPT-4 as a flexible and adaptable tool that can be refined to deliver optimal value in any given scenario.

By offering fine-tuning, OpenAI not only enhances GPT-4’s appeal but also reinforces the model’s role as a leading AI solution across diverse sectors. From startups seeking to automate niche tasks to large enterprises looking to scale intelligent systems, GPT-4’s fine-tuning capability provides a powerful resource for driving innovation.

OpenAI announced that fine-tuning GPT-4o will cost $25 for every million tokens used during training. After the model is set up, it will cost $3.75 per million input tokens and $15 per million output tokens. To help developers get started, OpenAI is offering 1 million free training tokens per day for GPT-4o and 2 million free tokens per day for GPT-4o mini until September 23. This makes it easier for developers to try out the fine-tuning service.

As AI continues to evolve, OpenAI’s focus on customization and adaptability with GPT-4 represents a critical step in making advanced AI accessible, scalable, and more aligned with real-world applications. This new capability is expected to accelerate the adoption of AI across industries, creating a new wave of AI-driven solutions tailored to specific challenges and opportunities.

GOOGLE

This Week in Search News: Simple and Easy-to-Read Update

Published

3 months ago

June 30, 2024

Entireweb News Bot

This Week in Search News: Simple and Easy-to-Read Update

Here’s what happened in the world of Google and search engines this week:

1. Google’s June 2024 Spam Update

Google finished rolling out its June 2024 spam update over a period of seven days. This update aims to reduce spammy content in search results.

2. Changes to Google Search Interface

Google has removed the continuous scroll feature for search results. Instead, it’s back to the old system of pages.

3. New Features and Tests

Link Cards: Google is testing link cards at the top of AI-generated overviews.
Health Overviews: There are more AI-generated health overviews showing up in search results.
Local Panels: Google is testing AI overviews in local information panels.

4. Search Rankings and Quality

Improving Rankings: Google said it can improve its search ranking system but will only do so on a large scale.
Measuring Quality: Google’s Elizabeth Tucker shared how they measure search quality.

5. Advice for Content Creators

Brand Names in Reviews: Google advises not to avoid mentioning brand names in review content.
Fixing 404 Pages: Google explained when it’s important to fix 404 error pages.

6. New Search Features in Google Chrome

Google Chrome for mobile devices has added several new search features to enhance user experience.

7. New Tests and Features in Google Search

Credit Card Widget: Google is testing a new widget for credit card information in search results.
Sliding Search Results: When making a new search query, the results might slide to the right.

8. Bing’s New Feature

Bing is now using AI to write “People Also Ask” questions in search results.

9. Local Search Ranking Factors

Menu items and popular times might be factors that influence local search rankings on Google.

10. Google Ads Updates

Query Matching and Brand Controls: Google Ads updated its query matching and brand controls, and advertisers are happy with these changes.
Lead Credits: Google will automate lead credits for Local Service Ads. Google says this is a good change, but some advertisers are worried.
tROAS Insights Box: Google Ads is testing a new insights box for tROAS (Target Return on Ad Spend) in Performance Max and Standard Shopping campaigns.
WordPress Tag Code: There is a new conversion code for Google Ads on WordPress sites.

These updates highlight how Google and other search engines are continuously evolving to improve user experience and provide better advertising tools.

FACEBOOK

Facebook Faces Yet Another Outage: Platform Encounters Technical Issues Again

Published

7 months ago

March 20, 2024

Max

Uppdated: It seems that today’s issues with Facebook haven’t affected as many users as the last time. A smaller group of people appears to be impacted this time around, which is a relief compared to the larger incident before. Nevertheless, it’s still frustrating for those affected, and hopefully, the issues will be resolved soon by the Facebook team.

Facebook had another problem today (March 20, 2024). According to Downdetector, a website that shows when other websites are not working, many people had trouble using Facebook.

This isn’t the first time Facebook has had issues. Just a little while ago, there was another problem that stopped people from using the site. Today, when people tried to use Facebook, it didn’t work like it should. People couldn’t see their friends’ posts, and sometimes the website wouldn’t even load.

Downdetector, which watches out for problems on websites, showed that lots of people were having trouble with Facebook. People from all over the world said they couldn’t use the site, and they were not happy about it.

When websites like Facebook have problems, it affects a lot of people. It’s not just about not being able to see posts or chat with friends. It can also impact businesses that use Facebook to reach customers.

Since Facebook owns Messenger and Instagram, the problems with Facebook also meant that people had trouble using these apps. It made the situation even more frustrating for many users, who rely on these apps to stay connected with others.

During this recent problem, one thing is obvious: the internet is always changing, and even big websites like Facebook can have problems. While people wait for Facebook to fix the issue, it shows us how easily things online can go wrong. It’s a good reminder that we should have backup plans for staying connected online, just in case something like this happens again.