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Ashirase, a Honda incubation, reveals advanced walking assistance system for visually impaired

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Globally, 225 million people are estimated to suffer from moderate or severe visual impairments, and 49.1 million are blind, according to 2020 data from the Investigative Ophthalmology and Visual Science journal. A Japanese startup that was incubated at Honda Motor Company’s business creation program hopes to make navigating the world easier and safer for the visually impaired.

Ashirase, which debuted as the first business venture to come out of Honda’s Ignition program in June, shared details of its in-shoe navigation system for low-vision walkers on Tuesday. The system aims to help users achieve more independence in their daily lives by allowing them to feel which way to walk through in-shoe vibrations connected to a navigation app on a smartphone. Ashirase hopes to begin sales of the system, also named Ashirase, by October 2022.

Honda created Ignition in 2017 to feature original technology, ideas, and designs of Honda associates with the goal of solving social issues and going beyond the existing Honda business. CEO Wataru Chino had previously worked at Honda since 2008 on R&D for EV motor control and automated driving systems. Chino’s background is evident in the navigation system’s technology, which he said is inspired by advanced driver assist and autonomous driving systems.

“The overlap perspective can be, for instance, the way we utilize sensor information,” Chino told TechCrunch. “We use a sensor fusion technology, meaning we can combine information from the different sensors. I have experience in that field myself so that is helpful. Plus there is overlap with automated driving because when we were thinking of safety walking, the automated driving technology had given us an idea for the concept.”

“Ashirase” comes from the Japanese words ashi, meaning “foot,” and shirase, meaning “notification.” As its name suggests, the device, which is attached to the shoe, vibrates to provide navigation based on the route set within an app. Motion sensors, which consist of an accelerometer, gyro sensors and orientation sensors, enable the system to understand how the user is walking.

While en route outside, the system localizes the user based on global navigation satellite positioning information and data based on the user’s foot movement. Ashirase’s app is connected to a range of different map vendors like Google Maps, and Chino said the device can switch to adapt to different information available on different maps. This capability might be helpful if, say, one map had updated information about a road blockage and could send over-the-air updates.

“Going forward, we want to develop the function to generate a map itself using sensors from the outdoor environment, but that’s maybe five years down the line,” Chino said.

The vibrators are aligned with the foot’s nerve layer, so it’s easy to feel the pulse. To indicate the user should walk straight ahead, the vibrator positioned at the front of the shoe vibrates. Vibrators on the left and the right side of the shoe also indicate turning signals for the walker.

Ashirase says this form of intuitive navigation helps the walker attain a more relaxed state of mind rather than one that is constantly alert, leading to a safer walk and less stress for the user.

This also allows the user to have more attention to spare for audible warnings in their environment, like, for example, if they were at a crosswalk, because the device cannot warn the user of obstacles ahead.

“Going forward, we’re thinking about technical updates for users who are totally blind because they don’t have such information like obstacle awareness like low-vision people,” Chino said. “So at this moment, the device is designed for low-vision walkers.”

While indoors, like in a shopping mall, the GPS won’t reach the user, and there isn’t a map for them to localize to. To solve for this, the company says its plan is to use WiFi or Bluetooth-based positioning, connecting to other devices and cell phones within the store, to localize the visually impaired person.

Ashirase is also considering ways to integrate with public transit systems so that the device can alert a user if they have arrived or are near their next stop, according to Chino.

It’s a lot of tech to pack into one little device that attaches to a shoe — any shoe. Chino said the device, which only needs to be charged once a week based on three hours of use per day, is made to be flexible and fit onto different types, shapes and sizes of shoes.

Ashirase intends to release its beta version for testing and data collection in October or November this year and hopes to achieve mass production by October 2022. It’ll have a direct-to-consumer model, the price of which the company is not yet ready to disclose, and a subscription model, which should cost about 2,000 to 3,000 Japanese Yen ($18 to $27) per month.

Chino estimates it’ll take the company 200 million Yen ($1.8 million), including the funds the company has already raised, to make it to market. So far, the company has raised 70 million Yen ($638,000), which came in the form of an equity investor round and some non-equity rounds, according to Chino.

Honda maintains an investor role in the company, supporting and following the business along the way, but Ashirase’s aim is to go public as a standalone company.

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Source: https://techcrunch.com/2021/07/28/ashirase-a-honda-incubation-reveals-advanced-walking-assistance-system-for-visually-impaired/

Artificial Intelligence

Here’s How AI-backed Insurance Plans Make Your Life Easy

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You might be surprised to hear that AI is becoming more important in the field of insurance than ever. Insurance companies have been using AI and big data for underwriting and other functions for years.

As Gen Z is now beginning to make radical financial decisions for themselves, we’ve seen a rise in the number of platforms and applications that are now automating the process of insurance policies. With such platforms, powered by AI and data analysis techniques, insurance companies are slowly changing the way they function, bidding farewell to the pre-set traditional insurance schemes for people to choose from.

Most companies talk about the benefits of AI in marketing and management, but it can be essential in other aspects of the insurance industry as well. These new-age AI-backed insurance plans are making the consumers’ lives simpler and better, which has resulted in a stronger competitive advantage for insurance companies using it. Here’s how.

AI Provides Better Accessibility for Insurance Customers

What’s better than having all your essential finance-related documents and details in your hand at all times? These online platforms make it incredibly easy for you to get the required insurance quickly. It eliminates the tedious step of processing paperwork by simply automating getting customer details without you having to fill out numerous forms. 

Since you get your insurance entirely online, you don’t even need to carry around physical proof for the same. The platform gives you e-proofs for everything related to your insurance policies.

Artificial Intelligence Means it Takes Less Paperwork to Get Insured

We’ve all been there – tired from standing in long queues, figuring out complicated terms related to insurances, filling out forms while making sure not to make any mistakes; it’s draining and tiresome. But platforms such as Salty can help you.

These AI-backed insurance platforms allow you to move the process online, giving it access to your information which helps them suggest a personalized plan for you. All the necessary details are also stored online on cloud with maximum customer privacy and security to ensure your details are in the right hands. Once you’re done with the formalities, you’re insured. It’s just that simple.

With no in-hand documents or submission of the same to the company, you can enjoy the security of your insurance without the hassle of paperwork. This is especially beneficial when insuring utilities such as a house or vehicle.

Personalized Insurance Schemes

Gone are the days of traditional insurance schemes when people were bound to sacrifice some of their requirements to attain insurance through these rigid plans. Nowadays, insurance companies have integrated technologically advanced techniques into their architecture. This allows them to understand their customers through efficient data analysis truly. When you give them your basic details such as name, phone number, email address, etc., they read through your smart devices, transaction history, bank history, SMS, etc., to determine what kind of insurance plan would be ideal for your needs. 


This personalization of schemes has been made possible with AI allows customers to be in control of their money and safety.

Room For Customization

With personalization comes room for customization of these schemes! Insurance plans on such platforms allow customers to alter their plans based on recent changes easily. 

For instance, when a customer gets healthcare insurance, it covers their needs and is customized for their requirements. However, a new addition to the family or the demise of an older member calls for a change in the plan. They can alter their policy to cover their family members without a lot of hassle or paperwork by simply completing an online procedure. 

This is also incredibly useful when buying a costly home appliance or automobile as these utilities require insurance.

Flexibility When Choosing Plans

Designed to give the customer complete freedom, these AI-backed policies genuinely deliver what they promise. These plans aren’t solely for healthcare or life insurance; they can also be small-term, event-based, or utility-based. 

For instance, if you don’t get embedded insurance for an appliance as a native feature, you can buy utility-based insurance on a low premium; you can also get short-term insurance for a small business—the possibilities are endless.

Getting insurance can sound daunting. However, the new-age AI-driven platforms which leverage data analysis to provide you with the best customer experience make the process incredibly easy to grasp, fit for anybody seeking insurance.

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Source: https://www.smartdatacollective.com/how-ai-backed-insurance-plans-make-your-life-easy/

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Artificial Intelligence

The Ways Machine Learning Companies Can Redefine Insurance

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Most insurance companies tend to process only a small part of their data — around 10 to 15%. The rest of the data in their databases are not being processed adequately, meaning that they are probably missing on insights in the data they keep but never analyze.

However, in order to analyze the unstructured data that will help you bring on better business decisions and prevent intruder attacks, the use of advanced technology is needed. Machine learning comes to the scene here because it is able to analyze lots of structured, semi-structured, or completely unstructured data the insurance companies tend to store in their databases.

The benefits of machine learning are numerous:

● Understanding risk

● Understanding premium leakage

● Managing expenses

● Subrogation

● Litigation

● Fraud detection

Since insurance companies deal with a lot of sensitive data and assets, they need to have an efficient way of finding any fraudulent activities and preventing them. This will increase their trustworthiness in the eyes of current and potential clients.

Stick with us while we explain the possible challenges when it comes to machine learning before we jump to explaining how machine learning companies can be of use for insurance services providers.

Challenges of Applying Machine Learning

Just like any other new thing you are trying to apply and implement for the first time, machine learning also brings some specific challenges. The most important ones are listed and explained down below.

Every system needs to be trained and fed with data that stimulate and support various scenarios. But since it is impossible to cover every single scenario, it leads to the system having certain unavoidable loopholes.

For example, if the insurers are looking for an AI-powered system to implement in billing, it will require them to have a separate training system. This is where the issue comes up — you need to provide the aforementioned data in order to train the AI system, and sometimes that is not physically possible.

Data sources

In machine learning, the quantity of data you provide will play a great role in training the AI system. The more data you feed into the system, the better predictive models can be created. However, let’s not disregard the fact that not only the quantity but quality of data is also very important.

If you feed the system with bad data, the predictive models will not be of any value. The sources of the data need to be representative and relevant, to avoid any bias in the future.

One of the biggest challenges with machine learning is that it can be very hard to predict and calculate the expected ROI (return on investment). This happens because machine learning is a continuous process, so if you dig up some findings at the early stage of the project and calculate the budget you’ll need, this may not be relevant at later stages of the project.

This is because there might be some new findings in the process that will request additional funding. These new findings may influence the ROI.

Pros of Machine Learning

After explaining the potential challenges when it comes to machine learning, it is time to explain the pros of applying machine learning in insurance processes. Here are some of the areas where machine learning is being used in insurance:

Lapse management – Machine learning plays a great role in finding out what policies in insurance are very likely to lapse, so it helps to identify them and find a way to prevent them from lapsing.

Recommendation tool – Machine learning can analyze all the individual insurances and automatically provide the best one for the given situation.

Property analysis – If you are using machine learning in property insurance, you can utilize it to identify the areas that will potentially need maintenance. You can also use AI to schedule any maintenance in the future.

Fraud detection – Probably one of the biggest pros of machine learning and the reason why most insurance companies want to use AI. Fraud detection and prevention play a vital role in insurance due to the fact that insurance companies deal with a lot of personal data.

Personalization – AI can be used to create personalized offers for policyholders. This can improve customers’ experience because the offer will be based on their past history with the insurance provider, so it will be customized to their habits and possibilities.

Prediction – Machine learning can be used for various statistical purposes, like predicting certain types of behavior in the future. You can use it to create models regarding prices, budgeting, risks, etc. The possibilities are really endless.

As you can see, machine learning is used not only for fraud detection and underwriting — there are so many other useful features machine learning is being used for in insurance.

Image Credit: https://unsplash.com/photos/rg1y72eKw6o

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Source: https://datafloq.com/read/the-ways-machine-learning-companies-can-redefine-insurance/17967

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Artificial Intelligence

5 fintech startups that made a splash at FinovateFall

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Fintech startups are increasingly leaning on automation and artificial intelligence (AI) to develop new technologies for financial services institutions as lenders look to increase efficiencies across their organizations. Thirty-five fintech startups demonstrated their budding technology at FinovateFall on Tuesday in New York. The Auto Finance News editorial team compiled five that made an impression during […]

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Source: https://bankautomationnews.com/allposts/center-of-excellence/5-fintech-startups-that-made-a-splash-at-finovatefall/

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AI

Longtime VC, and happy Miami transplant, David Blumberg has a new $225 million fund

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Blumberg Capital, founded in 1991 by investor David Blumberg, has just closed its fifth early-stage venture fund with $225 million, a vehicle that Blumberg says was oversubscribed — he planned to raise $200 million — and that has already been used to invest in 16 startups around the world (the firm has small offices in San Francisco, New York, Tel Aviv and Miami, where Blumberg moved his family last year).

We caught up with him earlier this week to talk shop and he sounded almost ecstatic about the current market, which has evidently been good for returns, with Blumberg Capital’s biggest hits tied to Nutanix (it claims a 68x return), DoubleVerify (a 98x return at IPO in April, the firm says), Katapult (which went public via SPAC in July), Addepar (currently valued above $2 billion) and Braze (it submitted its S-1 in June).

We also talked a bit about his new life in Florida, which he was quick to note is “not a clone of Silicon Valley.” Not last, he told us why he thinks we’re in a “golden era of applying intelligence to every business,” from mining to the business of athletic performance.

More from our conversation, edited lightly for length and clarity, follows:

TC: What are you funding right now?

DB: Our last 30 to 40 deals have basically been about big data that’s been analyzed by artificial intelligence of some sort, then riding in a better wrapper of software process automation on rails of internet and mobility. Okay, that’s a lot of buzzwords.

TC: Yes.

DB: What I’m saying is that this ability to take raw information data that’s either been sitting around and not analyzed, or from new sources of data like sensors or social media or many other places, then analyze it and take it to all these businesses that have been there forever, is beginning to [have] incremental [impacts] that may sound small [but add up].

One of our [unannounced] companies applies AI to mining — lithium mining and gold and copper — so miners don’t waste their time before finding the richest vein of deposit. We partner with mining owners and we bring extra data that they don’t have access to — some is proprietary, some is public — and because we’re experts at the AI modeling of it, we can apply it to their geography and geology, and as part of the business model, we take part of the mine in return.

TC: So your fund now owns not just equity but part of a mine?

DB: This is evidently done a lot in what’s called E&P, exploration and production, in the oil and gas industry, and we’re just following a time-tested model, where some of the service providers put in value and take out a share. So as we see it, it aligns our interests and the better we do for them, the better they do.

TC: This fund is around the same size of your fourth fund, which closed with $207 million in 2017. How do you think about check sizes in this market?

DB: We write checks of $1 million to $6 million generally. We could go down a little bit for something in a seed where we can’t get more of a slice, but we like to have large ownership up front. We found that to have a fund return at least 3x — and our funds seem to be returning much more than that — [we need to be math-minded about things].

We have 36 companies in our portfolio typically, and 20% of them fail, 20% of them are our superstars and 60% are kind of medium. Of those superstars, six of them have to return $100 million each in a $200 million fund to make it a $600 million return, and to get six companies to [produce a] $100 million [for us] they have to reach a billion dollars in value, where we own 10% at the end.

TC You’re buying 10% and maintaining your pro rata or this is after being diluted over numerous rounds?

DB: It’s more like we want 15% to 20% of a company and it gets [diluted] down to 10%. And it’s been working. Some of our funds are way above that number.

TC: Are all four of your earlier funds in the black?

DB: Yes. I love to say this: We have never, ever lost money for our fund investors.

TC: You were among a handful of VCs who were cited quite a lot last year for hightailing it out of the Bay Area for Miami. One year into the move, how is it going?

DB: It is not a clone of Silicon Valley. They are different and add value each in their own way. But Florida is a great place for our family to be and I find for our business, it’s going to be great as well. I can be on the phone to Israel and New York without any time zone-related problems. Some of our companies are moving here, including one from Israel recently, one from San Francisco and one from Texas. A lot of our LPs are moving here or live here already. We can also get up and down to South America for distribution deals more easily.

If we need to get to California or New York, airplanes still work, too, so it hasn’t been a negative at all. I’m going to a JPMorgan event tonight for a bunch of tech founders where there should be 150 people.

TC: That sounds great, though how did you feel about summer in Miami?

DB: We were in France.

Pictured above, from left to right: Firm founder David Blumberg, managing director Yodfat Harel Buchris, COO Steve Gillan and managing director Bruce Taragin.

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Source: https://techcrunch.com/2021/09/17/longtime-vc-and-happy-miami-resident-david-blumberg-has-raised-a-new-225-million-fund/

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