Android's latest update improves text-to-speech, Circle to Search, earthquake alerts and more

Image Credits: Google

Android introduced five updates on Tuesday as part of its latest release of the mobile operating system. Available for smartphones, tablets, and Wear OS watches, the new features include audio descriptions of images, text-to-speech technology for web pages in Chrome, and the ability to look up songs with “Circle to Search,” among other things. 

Initially announced in May, all Android users are officially getting “TalkBack,” an accessibility feature for people who are blind or have low vision. The feature is Google’s version of a screen reader, which provides detailed audio descriptions of digital images. TalkBack is powered by Gemini Nano, Google’s large-language-model-based platform. Users can now hear descriptions of all sorts of images, like online products, photos in their camera roll, or pictures in text messages. 

Another new accessibility feature is “Listen to this page,” which allows users to listen to webpages in the Chrome browser, whether that’s a blog post, news article, or recipe. The feature is helpful for those who are blind or have a learning disability, and people who prefer listening over reading. Users can pause, rewind, and fast forward, as well as set their preferred listening speed and the type of language and voice. It supports several languages, including English, French, German, Arabic, Hindi, and Spanish.

Google’s Circle to Search feature, which was announced earlier this year, enables users to search from anywhere on their phone by making gestures like circling, highlighting, scribbling, or tapping. The feature now allows Android users to search for songs via a new music button, eliminating the need to open a third-party app like Shazam. Users can simply activate Circle to Search by long pressing the home button or navigation bar. 

The new music capability can identify songs playing from the phone or in the background through nearby speakers. In addition to displaying the track name and artist, it also directs them to music videos via the YouTube app. 

According to some Reddit users, the music capability has been gradually rolling out to Samsung device users for a few weeks now. 

Android’s earthquake alert system has been available for some time. However, it’s now expanding to all U.S. states and its six territories. It was first launched in California in 2020, and it uses smartphone sensors to detect tremors and help people prepare for natural disasters and emergencies. For earthquakes of a magnitude of 4.5 or higher, Android sends out two types of warning alerts, either giving you a heads-up about a light amount of shaking or an alert recommending more immediate action if it detects extreme shaking.  

Android smartwatch users can use offline maps, a Google Maps capability for people to get around if they leave their phone behind, get lost, or find themselves without cell phone service. Watch OS also launched two new shortcuts to allow users to search for destinations using their voice or quickly tap the watch face to see where they are on the map. 

These features are launching alongside Android 15, which will roll out to more devices later this year, including Pixel devices. 

Yelp's Examples of Accessibility Attribute Searches

Yelp updates app with AI-powered alt text for images and new accessibility identifiers for businesses

Yelp's Examples of Accessibility Attribute Searches

Image Credits: Yelp

Yelp is rolling out an app update to include more accessibility identifiers for businesses, improved screen-reader experiences, and AI-powered alt text for images.

The company said that from 2020 to 2023, there has been an average rise of 40% in searches for “wheelchair accessible” places. With the new update, the company is adding eight more attributes across mobility, hearing, and vision to businesses to indicate how they are being accessible.

Yelp partnered with Disability:IN, the American Association of People with Disabilities (AAPD), Open to All, and The Arc to define these attributes.

Mobility

The company is following guidelines from the Americans with Disabilities Act of 1990 (ADA) to define accessible parking near the entrance to a business. Yelp is also adding an ADA-compliant main entrance attribute that has a ramp or elevators and doesn’t have any steps or stairs at an entrance. Plus, the door should have a clear opening width of at least 32 inches when opened at 90 degrees.

An ADA-compliant restroom should have an accessible path, grab bars, and turning space of at least 60 inches in diameter. Businesses can also indicate that they don’t have any steps or stairs at the entrance or inside the premises.

Businesses on Yelp can now add more accesible attributes.
Image Credits: Yelp

Hearing

If businesses have at least one staff proficient in American Sign Language (ASL) available during opening hours, they can add an “ASL Proficient” badge. Plus, restaurants and nightlife places can also indicate if one of the TVs shows closed captions with the content on the screen.

Vision

Restaurants and nightlife businesses can show if they have braille menus available on request. They can also show if they have digital menu available through a QR code so users can access it better on the devices with tools like screen readers.

Users can easily search for places with terms like “braille menus” or “ASL proficient” to search for establishments that meet these criteria.

Businesses can select accessible attributes
Image Credits: Yelp

What’s more, the company is also adding an Accessibility Resource Hub to help businesses become more inclusive.

Yelp is also leveraging large language models (LLMs) to generate alt text for images on the screen. This feature is rolling out on desktop first, with cross-platform availability planned for a future release. The company is making its site and the app better suited for screen readers, as well as enhancing navigation and improved contrast.

Yelp is launching a new AI assistant to help you connect with businesses

Napkin turns text into visuals with a bit of generative AI

Napkin

Image Credits: Napkin

We all have ideas, but effectively communicating them and winning people over is no easy feat. So how can we best accomplish this in an era of information overload and shrinking attention spans?

If you’re engineers Pramod Sharma and Jerome Scholler, you use Napkin, a new “visual AI” platform that the two built together. Napkin is launching out of stealth today with $10 million in funding from Accel and CRV.

Napkin was born out of Sharma’s and Scholler’s frustration with the endless number of documents and presentation decks that have become the norm in the corporate world. Before starting Napkin, Sharma, an ex-Googler, founded educational games company Osmo. Scholler was on Osmo’s founding team and, before that, had stints at Ubisoft, LucasArts and Google.

“Napkin’s core product is targeted toward marketers, content creators, engineers and professionals in the business of selling ideas and creating content,” Sharma told TechCrunch. “The goal is to minimize the time and headache of the design process by turning it into a mostly generative flow.”

“Generative” refers to generative AI. Yes, Napkin’s yet another company betting on the potential of the tech and joins a long, long list. But a few things stand out about the experience, which is strictly web-based for now.

With Napkin, users begin with text — a presentation, outline or some other document along those lines — or have the app generate text from a prompt (e.g. “An outline for best practices for a hiring interview”). Napkin then creates a Notion-like canvas with that text, then appends a “spark icon” to paragraphs of text that, when clicked, transform the text into customizable visuals.

These visuals aren’t limited to images, spanning different styles of flowcharts, graphs, infographics, Venn diagrams and decision trees. Each of these images contains icons that can be swapped out for another in Napkin’s gallery, and you get connectors that can visually link two or more concepts, too. The colors and fonts are editable, and Napkin offers “decorators” such as highlights and underlines to spruce up any element’s appearance.

Once finished, visuals can be exported as PNG, PDF or SVG files, or as a URL that links to the canvas where they were created.

“Unlike existing tools that are adding a generative component to an existing editor, we focus on generation-first experience where editing is added to complement the generation and not other way round,” Sharma said.

I took Napkin for a brief spin to get a sense of what it could do.

At the document creation step, out of a sense of morbid curiosity, I tried to get Napkin to generate something controversial, like “Instructions to murder someone” or “A list of extremely offensive insults.” Whatever AI Napkin is using wouldn’t tell me how to commit murder, but it did comply with the latter request — albeit with an addendum about how the insults were “intended for educational purposes.” (There’s a button in the canvas screen to report this type of AI misbehavior.)

Mischief managed, I threw a TechCrunch article into Napkin — a draft of this one to be precise. And, well, it quickly became apparent where Napkin’s strengths and weaknesses lie.

Napkin does best with simple descriptions, broad strokes of ideas, and narratives with clearly established timelines. The simplest way to put it is, if an idea reads like it could be better illustrated in a visual, Napkin will more often than not rise to the occasion.

Napkin
Image Credits: Napkin

When the text is a bit more nebulous, Napkin grasps at straws, sometimes generating visuals that aren’t grounded in that text at all. Take a look at the one below, for example – it verges on nonsensical.

Napkin
Image Credits: Napkin

For the visual below, Napkin invented pros and cons out of whole cloth (as generative models are wont to do). Nowhere in the paragraph did I mention privacy issues or Napkin’s learning curve.

Napkin
Image Credits: Napkin

Napkin occasionally suggests images or artwork for visuals. I asked Sharma if users might have to worry about the copyright implications of these, and he said that Napkin doesn’t use any public or IP-protected data to generate pictures. “It’s internal to Napkin so users don’t have to worry about rights on generated content,” he added.

Napkin
Image Credits: Napkin

I couldn’t help but notice that Napkin’s visuals all abide by a pretty generic, homogenous design language. Some early users of Microsoft’s generative AI features for PowerPoint have described the results from that software as “high school-level,” and the Napkin demo couldn’t help but bring those comments to my mind.

That’s not to suggest some of this isn’t fixable. It’s still early days for Napkin, after all — the platform has plans to launch paid plans, but not anytime soon — and the team is a bit resource-constrained by its size. There’s 10 people at Los Altos-based Napkin at present, and it plans to grow to 15 by the end of the year.

Moreover, few could suggest that Sharma and Scholler aren’t successful entrepreneurs, having sold Osmo to Indian edtech giant Byju’s for $120 million in 2019. Accel’s Rich Wong backed Napkin partly because he was impressed by Osmo’s exit — Wong was also an early investor in Osmo.

“Jerome and Pramod have an uncanny ability to take something incredibly challenging from a technical perspective and make it easy for users,” Wong said in a statement. “As a partner to their first company, Osmo, we watched them bring their vision for a new play movement to life with reflective AI. We are excited to support this new chapter as Napkin brings visual AI to business storytelling.”

Sharma says the proceeds from the $10 million round will be put toward product development and hiring AI engineers and graphic designers.

“All of our energy and resources will be going toward how Napkin can generate the most relevant and compelling visuals given text content,” he said. “There are endless ways to visualize and design. We are investing capital on building this depth and improving AI quality.”

Napkin turns text into visuals with a bit of generative AI

Napkin

Image Credits: Napkin

We all have ideas, but effectively communicating them and winning people over is no easy feat. So how can we best accomplish this in an era of information overload and shrinking attention spans?

If you’re engineers Pramod Sharma and Jerome Scholler, you use Napkin, a new “visual AI” platform that the two built together. Napkin is launching out of stealth today with $10 million in funding from Accel and CRV.

Napkin was born out of Sharma’s and Scholler’s frustration with the endless number of documents and presentation decks that have become the norm in the corporate world. Before starting Napkin, Sharma, an ex-Googler, founded educational games company Osmo. Scholler was on Osmo’s founding team and, before that, had stints at Ubisoft, LucasArts and Google.

“Napkin’s core product is targeted toward marketers, content creators, engineers and professionals in the business of selling ideas and creating content,” Sharma told TechCrunch. “The goal is to minimize the time and headache of the design process by turning it into a mostly generative flow.”

“Generative” refers to generative AI. Yes, Napkin’s yet another company betting on the potential of the tech and joins a long, long list. But a few things stand out about the experience, which is strictly web-based for now.

With Napkin, users begin with text — a presentation, outline or some other document along those lines — or have the app generate text from a prompt (e.g. “An outline for best practices for a hiring interview”). Napkin then creates a Notion-like canvas with that text, then appends a “spark icon” to paragraphs of text that, when clicked, transform the text into customizable visuals.

These visuals aren’t limited to images, spanning different styles of flowcharts, graphs, infographics, Venn diagrams and decision trees. Each of these images contains icons that can be swapped out for another in Napkin’s gallery, and you get connectors that can visually link two or more concepts, too. The colors and fonts are editable, and Napkin offers “decorators” such as highlights and underlines to spruce up any element’s appearance.

Once finished, visuals can be exported as PNG, PDF or SVG files, or as a URL that links to the canvas where they were created.

“Unlike existing tools that are adding a generative component to an existing editor, we focus on generation-first experience where editing is added to complement the generation and not other way round,” Sharma said.

I took Napkin for a brief spin to get a sense of what it could do.

At the document creation step, out of a sense of morbid curiosity, I tried to get Napkin to generate something controversial, like “Instructions to murder someone” or “A list of extremely offensive insults.” Whatever AI Napkin is using wouldn’t tell me how to commit murder, but it did comply with the latter request — albeit with an addendum about how the insults were “intended for educational purposes.” (There’s a button in the canvas screen to report this type of AI misbehavior.)

Mischief managed, I threw a TechCrunch article into Napkin — a draft of this one to be precise. And, well, it quickly became apparent where Napkin’s strengths and weaknesses lie.

Napkin does best with simple descriptions, broad strokes of ideas, and narratives with clearly established timelines. The simplest way to put it is, if an idea reads like it could be better illustrated in a visual, Napkin will more often than not rise to the occasion.

Napkin
Image Credits: Napkin

When the text is a bit more nebulous, Napkin grasps at straws, sometimes generating visuals that aren’t grounded in that text at all. Take a look at the one below, for example – it verges on nonsensical.

Napkin
Image Credits: Napkin

For the visual below, Napkin invented pros and cons out of whole cloth (as generative models are wont to do). Nowhere in the paragraph did I mention privacy issues or Napkin’s learning curve.

Napkin
Image Credits: Napkin

Napkin occasionally suggests images or artwork for visuals. I asked Sharma if users might have to worry about the copyright implications of these, and he said that Napkin doesn’t use any public or IP-protected data to generate pictures. “It’s internal to Napkin so users don’t have to worry about rights on generated content,” he added.

Napkin
Image Credits: Napkin

I couldn’t help but notice that Napkin’s visuals all abide by a pretty generic, homogenous design language. Some early users of Microsoft’s generative AI features for PowerPoint have described the results from that software as “high school-level,” and the Napkin demo couldn’t help but bring those comments to my mind.

That’s not to suggest some of this isn’t fixable. It’s still early days for Napkin, after all — the platform has plans to launch paid plans, but not anytime soon — and the team is a bit resource-constrained by its size. There’s 10 people at Los Altos-based Napkin at present, and it plans to grow to 15 by the end of the year.

Moreover, few could suggest that Sharma and Scholler aren’t successful entrepreneurs, having sold Osmo to Indian edtech giant Byju’s for $120 million in 2019. Accel’s Rich Wong backed Napkin partly because he was impressed by Osmo’s exit — Wong was also an early investor in Osmo.

“Jerome and Pramod have an uncanny ability to take something incredibly challenging from a technical perspective and make it easy for users,” Wong said in a statement. “As a partner to their first company, Osmo, we watched them bring their vision for a new play movement to life with reflective AI. We are excited to support this new chapter as Napkin brings visual AI to business storytelling.”

Sharma says the proceeds from the $10 million round will be put toward product development and hiring AI engineers and graphic designers.

“All of our energy and resources will be going toward how Napkin can generate the most relevant and compelling visuals given text content,” he said. “There are endless ways to visualize and design. We are investing capital on building this depth and improving AI quality.”

Yelp updates app with AI-powered alt text for images and new accessibility identifiers for businesses

Yelp's Examples of Accessibility Attribute Searches

Image Credits: Yelp

Yelp is rolling out an app update to include more accessibility identifiers for businesses, improved screen-reader experiences, and AI-powered alt text for images.

The company said that from 2020 to 2023, there has been an average rise of 40% in searches for “wheelchair accessible” places. With the new update, the company is adding eight more attributes across mobility, hearing, and vision to businesses to indicate how they are being accessible.

Yelp partnered with Disability:IN, the American Association of People with Disabilities (AAPD), Open to All, and The Arc to define these attributes.

Mobility

The company is following guidelines from the Americans with Disabilities Act of 1990 (ADA) to define accessible parking near the entrance to a business. Yelp is also adding an ADA-compliant main entrance attribute that has a ramp or elevators and doesn’t have any steps or stairs at an entrance. Plus, the door should have a clear opening width of at least 32 inches when opened at 90 degrees.

An ADA-compliant restroom should have an accessible path, grab bars, and turning space of at least 60 inches in diameter. Businesses can also indicate that they don’t have any steps or stairs at the entrance or inside the premises.

Businesses on Yelp can now add more accesible attributes.
Image Credits: Yelp

Hearing

If businesses have at least one staff proficient in American Sign Language (ASL) available during opening hours, they can add an “ASL Proficient” badge. Plus, restaurants and nightlife places can also indicate if one of the TVs shows closed captions with the content on the screen.

Vision

Restaurants and nightlife businesses can show if they have braille menus available on request. They can also show if they have digital menu available through a QR code so users can access it better on the devices with tools like screen readers.

Users can easily search for places with terms like “braille menus” or “ASL proficient” to search for establishments that meet these criteria.

Businesses can select accessible attributes
Image Credits: Yelp

What’s more, the company is also adding an Accessibility Resource Hub to help businesses become more inclusive.

Yelp is also leveraging large language models (LLMs) to generate alt text for images on the screen. This feature is rolling out on desktop first, with cross-platform availability planned for a future release. The company is making its site and the app better suited for screen readers, as well as enhancing navigation and improved contrast.

Yelp is launching a new AI assistant to help you connect with businesses

Illustration showing creating text from images.

Writer's latest models can generate text from images, including charts and graphs

Illustration showing creating text from images.

Image Credits: wongmbatuloyo / Getty Images

As generative AI continues to dominate the headlines, it’s hard sometimes to find actual working business use cases among the hype. Writer is a San Francisco startup that is working to create generative AI writing products with the enterprise in mind. Today, the company announced a new capability for its Palmyra model that generates text from images, including graphs and charts, they call Palmyra-Vision.

May Habib, company co-founder and CEO, says that they made a strategic decision to concentrate on multimodal content, and being able to generate text from images is part of that strategy. “We are going to be focused on multimodal input, but text output, so text generation and insight that is delivered via text,” Habib told TechCrunch.

By following that guiding star, the company decided to analyze images, rather than produce them (at least for now). She reserves the right to create charts and graphs at some point from data, but that’s not something they are doing at the moment. This particular release is focused on generating text from those kinds of images.

The company uses a multiple model approach to produce the Palmyra-Vision results, where each model has a specific job to do in determining what is in the image and then generating the text with four nines of accuracy, according to Habib.

This has a number of use cases, including an e-commerce website generating text from thousands of changing images to populate the website with the latest merchandise without having a human keep up with every change, or interpreting key takeaways from charts and graphs automatically. Another example is compliance checking. For instance, a pharmaceutical company could use Palmyra-Vision to perform an automated FDA compliance check against ad copy, making sure that the ad is compliant with FDA regulations as outlined in an associated document, as in the example below.

Writer Palmyra Vision example for pharma company checking ad against a document with FDA requirements.
Palmyra-Vision example for pharma company checking ad against a document with FDA requirements. Image Credits: Writer

Finally the product can interpret and summarize handwritten notes into text, but Habib says that it requires training the model for individual use cases such as medical or insurance, so that the accuracy is there.

Habib says that she does not recommend using these tools without a human review as part of the workflow. She believes this is absolutely essential because any model can hallucinate (make things up) or simply get facts wrong, and it’s important to have people checking the results. While they always recommend this to every customer, and most understand it at this point, she believes that it’s eventually going to require a more automated workflow to make it happen consistently across customers, something she says they are working toward.

The company has raised $126 million to date, per Crunchbase data, and is currently talking to the big cloud infrastructure platforms about partnering as they attempt to scale the company. Its most recent round was a $100 million Series B last September led by Iconiq.

The latest Palmyra release with the image to text capabilities is available starting today.

Writer nets $100M for its enterprise-focused generative AI platform