Upflow, a French startup we’ve been covering for quite a while, originally focused on managing outstanding invoices. The company is now announcing a shift in its strategy to become a B2B payment platform with its own payment gateway to complement its accounts receivable automation solution.

Like many software-as-a-service products, Upflow started by building a central hub specifically designed for one job in particular: CFOs. From the Upflow dashboards, CFOs and finance teams could see all their company’s invoices, track payments, communicate with team members, and send reminders to clients.

It integrates nicely with other financial tools and services to automatically import data from those third-party services. And a tool like Upflow can be particularly important as many tech companies struggle to raise their next funding round and want to improve their cash balance.

But that was just the first step in a bigger roadmap.

“Basically, my vision has always been that the real problem is payment methods,” Upflow co-founder and CEO Alexandre Louisy (pictured above) told TechCrunch. “Today, when you pay in a store, you pay with your phone. When you pay for your Spotify subscription or your Amazon subscription, you don’t even think about how you pay.”

“But when you look at B2B payments, the way you pay today hasn’t changed in the last 50 years. And for us, that’s why people struggle with late payments. The thing I’m really trying to fight against is the idea that late payments are linked to bad payers.“

According to him, around 90% of B2B payments still happen offline in the U.S. It’s still mostly paper checks. In Europe, it’s a different story as companies have adopted bank transfers. But transfers “are completely unstructured and require manual reconciliation,” Louisy said.

Upflow sells its accounts receivable automation software tool to midsized companies with a revenue between $10 million and $500 million per year. The company’s biggest client generates around $1 billion in annual revenue.

“But when you ask [CFOs], ‘What’s your strategy for setting up direct debit on part of your customer base?’ They don’t have a solution,” Louisy said.

Upflow helps you set up incentive strategies so that a portion of your client base moves to online payments, such as card payments or direct debits. The idea isn’t that all your clients are going to pay with a business card overnight. But Upflow can help you change the payment method for something like 20% or 30% of your client base.

Just like CRMs help you manage your sales processes with clients, Upflow now wants to be a financial relationship management (FRM) solution. It’s an interesting strategy as it shows how a startup like Upflow is thinking about diversifying its revenue sources.

“With our model shift, we’re moving from a model where we are 100% based on SaaS revenue to a hybrid model where we have SaaS revenue and payment revenue because we have our own payment gateway that we’ve set up with Stripe,” Louisy said.

Payment is the second brick in Upflow’s product suite. Up next, the company plans to integrate financing options with B2B “buy now, pay later” payment methods on the supplier front and factoring for a company’s outstanding invoices.

“We evaluate solutions … that provide embedded finance,” Louisy said. ”It’s not our core business to perform risk assessment. On the other hand, what’s interesting is that we can bring them useful data for credit scoring that they don’t necessarily have when they just connect to one of our users’ accounts.”

Automatic emergency braking (AEB) isn’t perfect, but the technology is improving, according to a recent study conducted by AAA. The research comes on the heels of a new federal rule requiring all vehicles to have the most robust version of AEB by 2029.

AAA wanted to see how newer vehicles with AEB fared compared to older models with the technology. AEB uses forward-facing cameras and other sensors to automatically tell the car to apply the brakes when a crash is imminent. And according to the test results, newer versions of AEB are much better at preventing forward collisions than older versions of the tech.

The motorist group conducted its test on a private closed course using older (2017–2018) and newer versions (2024) of the same three vehicles: Jeep Cherokee, Nissan Rogue, and Subaru Outback. Each vehicle was tested at 12mph, 25mph, and 35mph to see how well AEB performed at different speeds. And a fake vehicle was placed in the middle of the road to see whether AEB could prevent a collision.

Unsurprisingly, the newer models performed a lot better than the older ones: 100 percent of the 2024 vehicles braked before a collision, as compared to 51 percent of the older vehicles.

Still, this more recent test only involved forward collisions. Past AAA studies found AEB to be ill-equipped at preventing other common types of crashes, like T-bone collisions and left turns in front of approaching vehicles.

“Since we began testing AEB in 2014, the advancements by automakers are commendable and promising in improving driver safety,” said Greg Brannon, director of automotive engineering research. “There is still significant work ahead to ensure the systems work at higher speeds.”

It was a positive sign that AEB is improving, considering the National Highway Traffic Safety Administration (NHTSA) finalized a new requirement for all light-duty vehicles to have robust AEB systems by 2029. Around 90 percent of vehicles on the road today come standard with AEB, but the new rule requires automakers to adopt a more robust version of the technology that can stop vehicles traveling at higher speeds and detect vulnerable road users, like cyclists and pedestrians, even at night.

Even so, automakers are scrambling to put the brakes on the new rule’s adoption. Earlier this year, the Alliance for Automotive Innovation, which represents most of the major automakers, sent a letter to NHTSA arguing that the final rule is “practically impossible with available technology” and urging the agency to delay its implementation.

Liquid Web has unveiled the launch of a new GPU hosting service designed to keep pace with growing high-performance computing (HPC) requirements.

The new offering will harness Nvidia GPUs and is catered specifically toward developers focused on AI and machine learning tasks, the company confirmed.

NASA astronaut Sunita Williams just turned 59 in space on Thursday. She celebrated her milestone birthday aboard the International Space Station (ISS), which is around 400 kilometres above Earth, for the second time. 

Earlier her birthday celebration took place during a 2012 mission. 

Since June 6, Sunita Williams along with NASA astronaut Barry ‘Butch’ Wilmore has been aboard the ISS as part of the Boeing Crew Flight Test mission. Due to technical issues with the Boeing Starliner spacecraft, their stay has been unexpectedly extended. 

They are expected to return in February 2025. 

On her special day, Williams took up the task of maintaining the space laboratory. 

Reportedly, Williams celebrated her birthday by replacing filters in the waste and hygiene compartment. She also performed the essential task with the help of NASA astronaut Don Pettit to ensure safe and healthy living conditions on the ISS. 

Williams participated in a conference with Mission Control in Houston, Texas. Williams also engaged in discussions with flight directors in Houston, collaborating with astronauts Wilmore and Frank Rubio to outline mission objectives and upcoming tasks. 

Sunita Williams also received birthday wishes from Bollywood stars along with loved ones and family. 

Saregama Official shared a heartwarming video on Instagram that featured a compilation video of famous Indian stars singing Happy Birthday in Hindi to the astronaut. 

The video began with filmmaker Karan Johar sending birthday wishes to Williams, followed by singers, Hariharan, Sonu Nigam, Neeti Mohan and Shaan Mukherji.

In 1998, after joining NASA’s astronaut program, Williams launched into space for the first time on December 9, 2006, during the STS-116 mission. 

As a flight engineer for Expeditions 14 and 15, Williams set multiple records, including over 29 hours of spacewalks and more than 195 days in orbit.

By piloting Boeing’s CST-100 Starliner’s first crewed test flight, Williams made history by successfully docking with the ISS despite facing technical challenges. 

It’s been four years since the robot wizards at Boston Dynamics declared its dog-like Spot robot ready for the workplace.

In that time, the quadruped robot has been trialed in various roles at a number of firms, including for factory mapping at Ford, safety inspections at a Kia auto plant, and radiation surveys for Dominion Energy.

Its latest gig is at a Michelin facility in Lexington, South Carolina, which manufactures tires and light trucks. A video (top) released by Boston Dynamics on Wednesday shows Spot making its way around the site, carrying out various tasks as part of a pilot program.

“We were like kids at Christmas when we first got Spot,” said Wayne Pender, a reliability manager at Michelin whose job it is to ensure that all of the facility’s equipment is running at optimal efficiency.

Ryan Burns, also a reliability manager, said it’s important to get ahead of equipment failures in order to avoid a plant shutdown. Spot helps out by scanning 350 locations with a thermal camera to see if any parts are overheating or performing differently in some other way. Using specially designed software called Orbit, Spot then processes the data and sends it to to its operators for final analysis. If an anomaly is spotted, a human technician is sent out to review the situation before a final decision is made on how to respond.

“From a technician standpoint, Spot going out and doing these routes eliminates a mundane task that humans are doing,” Burns said. “By Spot finding these anomalies and these issues, it gives the technician more time to go out and plan and schedule how they’re going to fix the problem versus going out, identifying, then trying to plan and schedule everything.”

Burns added that it would be ideal to have more Spots at the facility so that the company can improve its inspection procedures, leading to enhanced efficiency and greater output.

Boston Dynamics is continuing to develop Spot and refine its capabilities through various pilot programs and partnerships in the U.S. and beyond.

It’s getting harder to tell what’s been AI-generated on the internet, and that goes especially for AI-generated text. It’s much easier for AI to fake text than it is for audio, images, or videos. As such, watermarking said content seems like an impossible task. However, it seems that Google has a solution in the form of the SynthID Text tool.

Since AI is so convincing, it’s important to have tools to help people identify if a research paper was spat out by ChatGPT. While cheating on your college report is bad, it’s far from the most harmful thing you can do with AI-generated text. A major issue is the spread of misinformation and other harmful content.

This is where Google SynthID Text comes in

The companies giving us the most powerful AI chatbots are also trying to give us tools to help us identify when something was created by those chatbots. OpenAI developed and tested tools to help identify when something was created by ChatGPT, but the company hasn’t seen fit to release it.

Google, on the other hand, has blessed us with a watermarking tool. As the name suggests, this is a tool that people will be able to use to identify if a section of text is AI-generated. SynthID Text is freely available to developers and businesses starting today. We’re not sure if Google is going to release a user-facing tool for casual people to check if text is AI-generated.

Watermarking text?

This seems like something that should be pretty impossible to do. It’s easier to understand watermarking AI-generated images. However, text is much easier to edit. You can easily edit or paraphrase what text a chatbot produces. Google managed to find a way, but it’s not perfect.

This method has to do with what are called Tokens. If you’ve been around AI tools, then you’ve probably seen this term tossed around. When you use an AI tool, you’re inputting data and getting data as an output. For example, typing a prompt “write a story about a rabbit” into a chatbot and getting a 100-word story as a response.

Well, the text in your prompt is divided into what are called tokens. These are sections of words or entire words that you enter into a model to be broken down and analyzed. Your response is also made up of tokens.

Well, according to Google, when a model generates text, it gives each token a score based on how likely it is that it’ll be used in the response. What SynthID Text does is insert additional information into each token by “modulating the likelihood of tokens being generated.” Then, Google compares the score from the original model’s output to the adjusted score. The final pattern of these scores is then “compared with the expected pattern of scores for watermarked and unwatermarked text, helping SynthID detect if an AI tool generated the text or if it might come from other sources,” says Google.

Limitations

It’s a lot to take in, but the important thing to note is that it’s a pretty effective tool. The only thing is that this isn’t a watertight solution. SynthID Text isn’t as accurate when it comes to shorter bits of text. So, you’ll have more luck if someone wants to generate a novel or a college report, however, you’ll have trouble if it’s a piece of advertising copy.

Also, this tool will struggle with text that was translated from another language or rewritten. This makes sense, as this would basically change all of the tokens of the original text.

Along with that, responses to factual questions are also an issue for SynthID Text. This is because it’s hard to adjust the token scores without changing the actual factual information in the response. If you’re talking about the natural habitat of a certain bird, there’s very little that you can change in your response before you start changing actual facts.

In a bit of a surprising announcement, Google stated that this tool was integrated into Gemini months ago, and most of us didn’t even know. Hopefully, this tool will lead the way for other tools that will help us detect AI-generated content.