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Stockholm Syndrome and AI Autonomous Cars

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Like canaries in a coal mine, participants in self-driving car tests run the risk of being victimized by Stockholm Syndrome, thus masking potential safety issues. (GETTY IMAGES)

By Lance Eliot, the AI Trends Insider

You might be vaguely aware of the Stockholm Syndrome.

From time-to-time, the news media will refer to a situation as somehow invoking the famous case of what happened in the 1970’s in Stockholm, Sweden.

In that case, bank robbers in Stockholm took several hostages and holed-up in the bank vault for six days, refusing to come out and refusing to give up the hostages. Once the siege ended, the hostages surprisingly later on refused to testify against the kidnappers/robbers, and were generally supportive of their captors.

This certainly seemed like a curious outcome.

We would have expected that the kidnapped victims would be upset and likely quite angry toward their kidnappers, maybe even wanting some kind of extensive revenge or at least demonstrative punishment for the crime committed. The local police brought in an expert psychiatrist/criminologist that said it was an example of brainwashing.

A name arose of calling it the Stockholm Syndrome and it seems to have stuck ever since.

Background About The Stockholm Syndrome

It is characterized as usually involving a bond developing between the hostages and the captors. The hostages might start out as rightfully hostile toward the captors, and then gradually shift toward having positive feelings toward them. This often slowly emerges during the period of captivity and is not usually instantaneous.

After getting out of captivity, the hostages might continue to retain the sense of positive bond. At first, the bonding often is quite high, and then dissipates over time. Ultimately, the hostages might someday change their minds and begin to have more pronounced negative feelings toward the captors. This all depends on a number of factors, such as the treatment of the hostages during the captivity portion, the interaction with their captors afterward, and so on.

If you carefully consider the phenomena, it might not seem particularly strange that during captivity the hostages might bond with their captors.

One could say that this is a coping mechanism.

It might increase your odds of survival. It might also be a means to mentally escape the reality of the situation. It could also be a kind of personal acquiescence to the situation and especially if you believe that you might not ever escape. Various psychological explanations are possible.

What tends to really puzzle outsiders is that after captivity the hostages would continue to retain that positive bond. It would seem that if you gained your freedom, and you were no longer under the belief that you had no other choice for pure survival purposes, you would pretty quickly bounce back with rage or some other similar reaction. We’d all allow that maybe for the first few minutes or hours after getting out of captivity that you might still be mired in what had occurred, but after days or even weeks or months, we’d assume that the hostages would re-calibrate mentally and no longer have that false bonding muddled in their minds.

Some might say that the after-effect lasts because the hostage maybe wants to self-justify the earlier bonding.

In other words, if you bonded during captivity, maybe afterward you would be embarrassed to admit it was a mistake, so you keep it going to try and show that it all made sense all along. Another explanation is that the person is so brainwashed at the time of captivity that it remains nearly permanently affixed in their psyche. There are lots of theories about this. No one explanation seems to be the all-purpose way to rationalize it.

Some object to the references about the Stockholm Syndrome and believe that it has become a kind of scapegoat to explain all sorts of unusual psychological situations.

Some say it has been watered down due to overuse. Some say it never had a crisp definition to start with and has become a popular item that lacks bona fide professional psychological bases and uses. Some try to create variants by renaming it to a local situation like say the Los Angeles Syndrome or the Piccadilly Square Syndrome.

Admittedly, it’s a handy kind of reference paradigm that most people seem to know enough about that it can get their attention and interest.

Stockholm Syndrome And AI Autonomous Cars

Which brings us to the next point, namely, what does this have to do with AI self-driving driverless autonomous cars?

At the Cybernetic AI Self-Driving Car Institute, we are developing AI software for self-driving cars. As part of that effort, we’re also keenly interested in the trial tests of AI self-driving cars.

Google’s Waymo has one of the most well-publicized of the trial tests of AI self-driving cars. They have for example been using a selected area of Phoenix, Arizona that involves having everyday people making use of the Waymo self-driving cars. This is being done as a kind of experiment, or maybe you’d prefer to call it a Proof Of Concept (POC), or a pilot, or a test, or a trial run, or whatever. Cleverly, Waymo coined it the “Early Rider Program” and the participants are Early Riders. The naming seems to bring forth imaginary of mavericks, those that dare to be first, and it provides an obviously upbeat way to portray the program (reminiscent of the movie Easy Rider and the freewheeling imagery of motorcyclists).

Let’s clarify that those initial trial runs were not randomly picking people up off the street.

Even though these are genuinely public kinds of trial runs, the participants needed to first apply to the program.

Only those applicants then chosen by Waymo are then allowed to participate. You can say that it is open to anyone in the sense that anyone can apply. Merely pointing out that whatever selection criteria is used, it then becomes semi-selective out of the pool of whomever actually applies.

This is in contrast to say having AI self-driving cars roaming around and picking up anyone that happens to flag one down (which is something gradually starting to occur, including in other parts of the country too).

The stated purpose of the Early Rider Program was to provide an opportunity for residents in the geographical area to have access to these AI self-driving cars and provide feedback about them.

In that sense, you can imagine how exciting it might be to become a chosen participant.

You could help shape not only how Waymo is making AI self-driving cars, but maybe the entire future of AI self-driving cars.

And, the bragging rights would be awesome, including at the time of your participation and afterward. Imagine that you want to impress a date, and tell them you’ll swing over at 7:00 p.m. to take them to dinner. Lo and behold, you show-up in an AI self-driving car. Whoa, impressive! Or, some years from now, when presumably AI self-driving cars are everywhere, you chat with a stranger and mention that, yes, you were one of the original pioneers that helped shape AI self-driving cars. You act modestly as though it was no big deal, and when the person says that you were like Neil Armstrong or “Buzz” Aldrin, Jr., you smile and say that you were a bit of a risk taker in your early days.

Speaking of risks, how much risk are these participants taking on?

According to reports, the trial runs have had a back-up human driver from Waymo in the cars, thus, presumably, there has been a licensed driver ready to takeover if needed.

Presumably, this is not just any licensed driver, but one trained to keep their attention to the self-driving car and that is ready to step into the driving task when so needed. This definitely is intended to reduce the risks of the AI self-driving car going awry. But, this is also not necessarily a risk-free kind of ride, since there are numerous issues of having a so-called back-up driver and trying to co-share the driving task.

As recently indicated, the back-up driver will no longer be present in some rides and some locales.

See my article about the drawbacks of the co-sharing of driving with a back-up human driver: https://aitrends.com/selfdrivingcars/human-back-up-drivers-for-ai-self-driving-cars/

For my framework about AI self-driving cars, please see: https://aitrends.com/selfdrivingcars/framework-ai-self-driving-driverless-cars-big-picture/

Scope Of Trial Runs

In quick recap, a trial run of this nature consists of vendor selected people in a predetermined geographical area that are asked to participate in a kind of real-world experiment involving having AI self-driving cars transport them, doing so from time-to-time, as determined by the vendor.

It’s quite a bit different than having people come to a closed tracks or proving grounds to do trial runs, and so in that sense this is a bolder and more illuminating way to presumably get insightful feedback about AI self-driving cars.

For my article about the closed track areas for AI self-driving cars, see: https://aitrends.com/ai-insider/proving-grounds-ai-self-driving-cars/

One criticism is that these are indeed vendor selected participants, meaning that the auto maker or tech firm has chosen the people that are participating.

Suppose there is some kind of purposeful selection criteria that is weaning out certain kinds of people, or maybe a subliminal selection bias, in which case, whatever is learned during these trial runs is lopsided. It doesn’t presumably cover the full gamut of people.

Will the result be an AI self-driving car that has certain kinds of biases and those biases will be reflected in what AI self-driving cars do and how they behave?

For my article about hidden biases in AI self-driving cars, see: https://aitrends.com/ai-insider/debiasing-ai-self-driving-cars/

Another reported aspect is that the participants in such trial runs are required to sign NDA’s (Non-Disclosure Agreements).

This presumably restricts the participants from freely commenting to the public at large about their experiences of riding in these AI self-driving cars. You can certainly empathize with the automaker or tech firm that they want to keep the participants somewhat under-wraps about their newly emerging AI self-driving cars. Imagine if a participant makes an off-hand remark that they hate the thing and no one should ever ride in one. This could be a completely unfair and baseless statement, which would appear to have credence simply because the person was a participant in the trial runs.

There could also be proprietary elements underlying the AI self-driving cars that could be blurted out by a participant and undermine the secrecy of the Intellectual Property (IP) of the vendor. Right now, the AI self-driving car companies are in a fierce battle to see who can achieve this moonshot first.

There is already a lot of sneaking around to find out what other firms are doing.

There’s a potential treasure trove that you might be able to get a participant to unwittingly divulge.

For my article about the stealing of secrets about AI self-driving cars, see: https://aitrends.com/selfdrivingcars/stealing-secrets-about-ai-self-driving-cars/

For why this is considered a moonshot effort to create an AI self-driving car, see my article: https://aitrends.com/selfdrivingcars/self-driving-car-mother-ai-projects-moonshot/

There are some that think the auto makers and tech firms should not restrict the participants in any manner whatsoever.

They argue that it is important for the public to know what these participants feel about AI self-driving cars. Good or bad. Right or wrong. Blemishes or not. It is for the good of the public overall to know what the participants have to say.

Furthermore, they would likely claim that it will help the other automakers and tech firms too. In other words, if you believe that AI self-driving cars provide great benefits to society, the sooner we get there, the better for all of society. Thus, the more that the auto makers and tech firms share with each other, the sooner the benefits will emerge.

For my article about idealists and AI self-driving cars, see: https://aitrends.com/selfdrivingcars/idealism-and-ai-self-driving-cars/

For my article about the Frankenstein like potential dangers, see: https://aitrends.com/selfdrivingcars/frankenstein-and-ai-self-driving-cars/

To some degree, the participants in these kinds of trial runs have been periodically allowed to say something about their experiences.

You’ll see a quote in newspaper articles or magazines, or on some social media sites. Usually, it is a very carefully crafted indication, or at least one that has been vetted and approved for release by the automaker or tech firm. It is rarely a fully off-the-cuff, anything-you-want-to-say utterance.

This is again as a result of the NDA, and the automaker or tech firm wanting to try and shape the public perception of the matter.

You can imagine that if rocket makers tried to make rockets, and if their trial runs had issues, it could become a public relations nightmare if the tiniest imperfections were made known and then potentially blown out of proportion. This actually does happen. Companies trying to create some new technology will at times get clobbered by the fact that it isn’t working right, and yet they are aware that it is not yet ready for prime time, and hence their desire to run trials first. But, if the trials become the focus of attention, and if only having complete perfection is the public criteria (even during the trial runs), the trials really serve no useful purpose, since you would need to hold back from doing any trials at all, until the system was perfected anyway. It’s kind of a Catch-22.

Feedback Taken With A Grain Of Salt

Let’s though shift our attention to something else, but related to this whole topic.

At some of my recent presentations at industry conferences, I’ve been asked about some of the comments that participants in these trial runs have been saying so far.

The comments are usually quite glowing.

Even if there is a mention of something that went awry, the participants seem to then explain it away and the whole thing seems just peachy.

For example, a participant that reported an AI self-driving car that got somewhat lost in a mall parking lot trying to get to the rider’s desired destination, and later on the AI developers adjusted the system to instead go to a designated drop-off point. This is a lighthearted tale. No one was hurt, no apparent concern, other than maybe some excess time spent waiting for the AI self-driving car to find the proper spot. Plus, it was later fixed anyway.

Others with a more critical eye question these kinds of stories.

Shouldn’t we be concerned that the AI system wasn’t able to better navigate the mall parking lot?

Maybe there are other locations that it would have problems with too?

Shouldn’t we be concerned that the AI system itself wasn’t able to make a correction, and that instead it required human intervention by the developers?

If AI self-driving cars aren’t going to be self-corrective, it seems to undermine what we are expecting of Machine Learning and the abilities of the AI for self-driving cars? And so on.

In any case, here’s the question that I sometimes get asked – are these participants in these tryouts perhaps suffering from Stockholm Syndrome?

There are some that seem to be concerned that the apparently whitewashed commentary being provided by the trial run participants might be a form of Stockholm Syndrome.

Maybe the participants are being “brainwashed” into believing that the AI self-driving cars are fine and dandy. Perhaps this is coming out of then not by their own freewill, but by the droning of it into their heads.

I’ll admit that I was a bit taken aback the first time I was asked this question.

I believe my answer was, say what?

After some reflective thought, I pointed out that the “Stockholm Syndrome” is perhaps a misapplication in this case.

The commonly accepted notion of the Stockholm Syndrome is that you have some kind of hostages and some kind of captors.

I dare say, it doesn’t seem like these trial run participants are hostages.

They voluntarily agreed to participate.

They put themselves forth to become participants.

They weren’t grabbed up in the cover of darkness and thrown into AI self-driving cars.

So, I reject the notion that you can somehow compare these trial runs with a hostage-captor scenario.

The comparison might seem appetizing, especially if you are someone averse to the trial runs, or at least how you believe the trial runs are being run. It also has a clever stickiness to it, meaning that it could stick with the trial runs because it kind of sounds applicable on a surface basis.

Suppose I am going to create a new kind of ice cream. I ask for volunteers to taste it. Those that are volunteering are presumably already predisposed to liking ice cream. I select volunteers that are passionate about ice cream and really care for it. I then have them start tasting the ice cream. They like it, and it’s a flavor and type they’ve never before had a chance to try. They are excited to be one of the first. They also believe they are shaping the future of ice cream for us all.

If I did that, I think we’d likely expect that the participants are going to generally have glowing comments about the ice cream trial. They might even suppress some of the not so good aspects, especially if we right away modified the flavors based on their feedback. After the trial runs are over, suppose the ice cream goes into mass production. I would anticipate that the original volunteers are likely to continue to say that the ice cream was great.

Does this mean that they are suffering from the Stockholm Syndrome? Just because they bonded in a positive way, and kept that positive bonding later on? I think that strips out the essence of the Stockholm Syndrome, the hostage part of things. The mistreatment part of things.

The analogy or metaphor falls apart due to a key linking element that is not there.

During these trial runs of these emerging AI self-driving cars, if some of the participants get injured or killed due to the AI self-driving car, I’d be pretty shocked if that got covered up. I think we’d all know about it. One way or another, it would leak out. There would likely be lawsuits filed. Someone would leak it. An inquisitive reporter would find out about it. An anonymous tip would get posted on a blog. Etc.

I mention this aspect because for those that are concerned about the positive commentary to-date about these trial runs, I’m suggesting that if there is something really amiss, I think it will become known.

In spite of the assertion that the participants are brainwashed, I doubt that the brainwashing could be that good that it would curtail a reveal about something systematically wrong and life threatening.

I realize there are conspiracy theorists that might disagree with me, see my article about conspiracy theories about AI self-driving cars: https://aitrends.com/selfdrivingcars/conspiracy-theories-about-ai-self-driving-cars/

Recap And Conclusion

Overall, here’s my key thoughts on this matter:

  • Trial runs are a generally good thing for progress on AI self-driving cars, though some argue we are dangerously being turned into guinea pigs
  • Auto makers and tech firms need to remain vigilant to undertake these trial runs safely
  • Participants might be somewhat muted about things that go awry
  • Participants will likely be reporting publicly only upbeat aspects, which we should consider and also at times take with a bit of salt
  • Calamities during the trial runs are likely to get leaked out and so it is probably going to be difficult for vendors to keep a lid on issues
  • It is understandable why there are various controls related to the release of info about the trial runs
  • There does not seem to be any conspiratorial concerns on this (I’ll add “as yet” for those that holdout for a conspiracy)
  • Trying to say this is a Stockholm Syndrome seems to be an overreach

We’ll need to keep our eye on the autonomous car tryouts, including the passengers and their reactions.

Copyright 2020 Dr. Lance Eliot

This content is originally posted on AI Trends.

[Ed. Note: For reader’s interested in Dr. Eliot’s ongoing business analyses about the advent of self-driving cars, see his online Forbes column: https://forbes.com/sites/lanceeliot/]

Source: https://www.aitrends.com/ai-insider/stockholm-syndrome-and-ai-autonomous-cars/

Artificial Intelligence

Pros and Cons of Using AI in Your Hiring Process

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As with everything else in the world, there are pros and cons of using Artificial Intelligence (AI) tools to supplementing human resources management (HRM). AI seems to be stepping into every industry imaginable today, from autonomous cars to genomic diagnostics.

Data drives everything, yet as you can imagine, problems tend to arise when using AI tools in a genuinely neutral environment. They are natively blind to issues that seem overly influenced by society today, resulting in a potential clash with regulations or ethics.

Today we’ll examine some of the advantages and concerns towards more significant AI deployment in this multi-billion-dollar industry.

Benefits of AI in Hiring

While percentages vary, the importance of digital HR is well-recognized worldwide (source: Deloitte)

Before we begin, it should be clear that this discussion leans towards in-house engagement with full-time employees. For temporary talent engagement, using an existing freelance platform will be more cost-effective and efficient.

Less Potential for Human Bias

Regardless of guidelines, policy, or other factors, ensuring an utterly bias-free hiring process can be incredibly difficult. It’s a human trait to be biased towards certain aspects – in fact, a defining characteristic.

AI, on the other hand, is purely data-driven. As long as the intent is not present in the AI tool, it won’t introduce unnecessary characteristics into the hiring process. While data-driven assessment may sound a bit cold, it is impartial.

Speeds Up the Hiring Process

Recruitment times vary widely depending on role, industry, and other factors. Yet, it’s undeniable that you can speed up at least part of the process using AI tools. For example, you can use them to create or improve job descriptions, match applications with requirements, carry out candidate screening, and more.

Taking too long to connect with potential talent is something that can cost you dearly. Remember, while there are ample candidates, almost all of them will be applying to multiple companies. If your hiring process drags on, talented individuals may quickly get snapped up by the competition.

Reduce HR Expenditure

From start to finish, hiring new talent is expensive. An increasingly large number of HR tasks can quickly lead to ballooning staff costs simply for talent acquisition. By introducing AI tools, not only can you speed up the process (as discussed above), but repetitive tasks can be kept away from expensive HR personnel and reduce cost.

Remember that the cost of AI tools is often much less in the context of large companies. As your organization grows, it makes much more financial sense to replace rote tasks with automation. You may be surprised at the overall impact on ROI.

Lowers Chances of Talent Leaks

When HR is recruiting, the focus is often on specific roles that need filling. While some companies do keep applications on file, cross-matching doesn’t always occur for various reasons. This shortcoming can easily lead to talent leaks where a candidate suited for an alternative role is lost.

Cross-matching often gets neglected due to the amount of time consumed trying to match multiple candidates and roles. Rather than onboarding more HR to fill this gap, you can leverage AI for much faster results.

Matching a potentially leaked talent with alternative roles also saves on the future need to hire specifically for that purpose. Keep these identified talents on file, or simply hire them early in anticipation of filling a need.

Improve the Sourcing Process

The traditional hiring process makes extensive use of job agencies or boards. While this helps save time and money, AI tools can give you many of the capabilities these channels offer. For example, an AI scraper can collate data from many sources and assess them for suitability.

With a single tool, you gain access to a massive potential talent pool that may not directly apply for a vacancy in the company. In this aspect, AI tools are even more important given how well individuals today reduce their digital footprint.

Disadvantages of AI in Hiring

Increasing Regulation

Like many other IT-related elements, AI remains but a tool in the hiring process. Unless you take great care selecting these tools, some form of bias may remain. The reality is that regulation isn’t seeking to eliminate bias but to direct it towards the desired outcome.

Because of this, many countries often have some form of discrimination built into regulatory systems – for instance, mandates for specific proportions of gender, domestic versus expatriate labor, or other mandated ratios.

One example of this is New York’s proposed legislation to regulate AI algorithms allowed for use in the hiring process. Similar proposals also exist in the European Union, with initial legal frameworks already in draft.

There are also varying general guidelines on occasions, such as privacy laws concerning video interviews, data collection activities, and such. Since 2019 the US state of Illinois has regulated the use of AI in video interviews mandating disclosure and specific prohibitions.

Specific Areas of Challenge Exist

Professionals in many countries believe company culture is a strong influencer in their choice of employment. (source Deloitte)

AI and data often work well together and can introduce elements of analysis effectively as well. However, it isn’t perfect, and when assessing individuals, there may be some areas challenging to factor in and match.

Intangible factors are especially prominent in this area and can include company culture, values, and mission cohesion. If too much weight is placed on tangible areas of analysis, mismatches in this area can still result in poor hires.

The risk of this happening is exceptionally high if the AI algorithms deployed are less intelligent than optimal. For example, some AI algorithms do nothing more than field matching and are extremely poor in a human relationship context.

Lack of Transparency in the AI Industry

Most companies will rely on external sources for AI algorithms used in the hiring process. Unfortunately, like many commercial products, exactly how they work is often considered proprietary. The result is a high risk as they may introduce areas contrary to the company culture or legislation.

May Lower Company Image

People often have different attitudes towards the use of tech tools. These varying attitudes can mean alienating a proportion of potential candidates who prefer more direct human interaction with a prospective employer.

What makes things worse is that AI elements are often used in the first line of the hiring process. Only when data has been sorted are results provided to human recruiters to make the final judgments.

This prospective alienation may lead to a poor impression of the brand among prospective employees, which may spread in the community and be hard to counter should processes change in the future.

AI Recruiting Tools Currently Available

If you’d like to try some of the available AI recruitment tools, the good news is the abundance of choice. There’s a lot of noise in the industry, so picking the right one can be a long process for each company.

Some of the available are;

XOR – You can design this AI chatbot to fit perfectly with your brand and serve as the first line of interaction with prospective hires. It can be highly customized to reflect branding, possible queries, and more. Many big brands are already using XOR, including Ikea, McDonald’s, and Mars.

Arya – For something more comprehensive, Arya serves as a complete recruitment platform that can work relatively independently. At the same time, it offers recruiters the necessary features to reach out to candidates directly via the platform. Arya takes care of employee screening and can help drastically reduce the cost of hiring.

Seekout – If your company needs to reach out to extend the reach of HR, then Seekout is a solid choice. It’s a talent-sourcing platform capable of scouring a massive database to find candidates based on job descriptions. The scope and scale of Seekout make it more suited to enterprise-scale users.

PymetricsProfessionals today often make use of gamification in multiple professional settings. Pymetrics does that for hiring and adds behavioral science into the mix. The result is a very modern tool that most younger professionals can relate with easily as they take Pymetrics tests.

HireVue – Originally a video software, HireVue entered the AI recruitment space relatively late, in 2020. It offers a HR chatbot suite capable of end-to-end assistance in the recruitment process. The platform helps source, screen, and naturally act as a video interview system.

Final Thoughts: Will AI Replace Human Recruiters

As with most industries new to the adoption of technology, HR is currently in a state of flux. This state is partially due to transient technology coupled with developing regulations. Overall, AI at the moment won’t replace human recruiters.

Instead, they should be seen as valuable assets capable of lowering overall recruitment costs and process enhancement.

Image Credit: Photo by Alex Knight from Pexels

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Source: https://datafloq.com/read/pros-cons-using-ai-your-hiring-process/18105

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Ex-hedge fund manager’s startup hits $2B value

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Advance Intelligence Group, a technology startup led by former hedge fund manager Jefferson Chen, topped $2 billion in valuation after raising more than $400 million from investors led by SoftBank Vision Fund II and Warburg Pincus.

The central business district of Singapore. Photographer: Lauryn Ishak/Bloomberg Mercury

Northstar, Vision Plus Capital, Gaorong Capital and EDBI also joined the Series D financing round, the company said in a statement on Wednesday. Having boosted its valuation from about $400 million in 2019, Advance Intelligence is now one of the most valuable startups in Singapore.

The firm was co-founded by Chen, the 39-year-old former Farallon Capital Management executive who headed private investing in Greater China. Before that, he worked at Goldman Sachs Group Inc. where he was involved in initial public offerings and mergers and acquisitions of Asian companies including Baidu Inc.

Since its inception in 2016, Advance Intelligence has incubated a string of upstarts under its umbrella in the financial services and retail industries. They include big data company Advance.AI and e-commerce merchant service platform Ginee. Its Atome Financial has a “buy now, pay later” app Atome and digital lending platform Kredit Pintar in Indonesia.

“Our vision is to use the AI technology to transform two industries: financial services and retail,” Chen, Advance Intelligence’s chief executive officer, said in a video interview. “These two industries are highly correlated and intertwined. We are trying to put them together into one ecosystem.”

The startup is following in the footsteps of Sea Ltd., a Singapore-based tech startup that went on to become the most valuable company in Southeast Asia in about 10 years. Like Sea founder Forrest Li, Chen was born in China, became a Singaporean citizen and has an MBA from Stanford University. He’s also aiming to build a global business.

Advance Intelligence plans to use the fresh capital to invest in research and development, recruit talent and expand markets and products, Chen said. It has 1,500 employees and operates in 12 markets across South and Southeast Asia, Greater China, and Latin America.

Credit Suisse Group AG acted as exclusive placement agent for the funding round.

— By Yoolim Lee

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Source: https://bankautomationnews.com/allposts/retail/ex-hedge-fund-managers-startup-hits-2b-value/

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Future and Facts of Apps That You Need to Know

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Whether it’s Facebook, Whatsapp, or Uber, we can’t imagine our lives without apps anymore. Some people would even say that apps are a must for businesses today. What makes this so popular, and how should you approach app marketing? Let’s find out!

An app is a software designed to work on mobile devices such as smartphones and tablets. They allow users to do many things, from shopping online to playing games while on the go.

“One of the biggest advantages of apps is that they help companies save money by using fewer resources than websites and other offline mediums.” 

Data collected by app stores and statistics show that more and more people prefer using apps over traditional methods of getting information; in fact, 50% of Americans use their phones for research before making purchases, according to one study. But is it all smooth-sailing?

Note the details

As more and more daily tasks become mobile, app makers compete with each other for user attention and time. It’s quite hard to build a perfect app because so many people expect so much from them: we want apps that keep us up to date about the latest news, let us chat with friends and family, give us directions when we’re lost, track our fitness goals and help with shopping online. Providing such features requires a lot of time and money and lots of expertise that not every company has access to. That’s why some experts think that apps might be just a short-lived thing and will die out soon. But this doesn’t mean apps are bad for business!

App usage is still growing. App Annie’s revenue increased by about 70% in 2015 and surpassed $50 billion. The same report shows that there are more than 26 billion downloads every year. So, if you’re thinking of entering the mobile space or taking your existing business online, you should put some serious thought into building an app. Let’s look at how it works and what tools you need to create one yourself.

There are four main steps to creating an app: coming up with an idea, choosing a platform, making the prototype, and testing it. If you want to build an app on your own, it’s best not to start from scratch but to use free or paid tools that come with ready-made templates. Popular choices include the Phonegap building tool, Appcelerator, and Xamarin. However, there are alternatives to these which might be even better for your needs. For example, if you want to save some money, you could use Python instead of C# because the former is free while the latter requires purchasing a license, check RemoteDBA to know more

Interesting Facts about Apps

If you have an app idea but lack the expertise or time needed to create it yourself, you can always hire professional app makers. They will make everything from scratch and help grow your business by meeting set objectives. Prices vary depending on what your app does and how complex it is; we recommend starting with $25000 and going up from there.

The average price for a good design ranges from $5000-8000. Before starting to code the app, you need a special UX/UI designer who can foresee all potential problems and put everything for you. They will develop a detailed plan that will include the actual cost since this part of development is quite expensive, too, especially if you want your app to be original and creative 

If you decide to make an app yourself, it pays off to get some help from assistants or co-workers. You can even hire virtual workers from India or Bangladesh – they are very cheap, have extensive experience in the software industry, and know-how to work remotely, which means it’s easy to coordinate with them. A good developer charged by the hour will cost you about $15-20, while a virtual assistant from Dhaka costs around $3 per hour.

Customers often prefer virtual workers who don’t have time to deal with various issues and processes involved in company administration. Using services like Upwork or Freelancer allows businesses to get rid of this trouble forever!

After getting a functional app, you might want to engage in some advertising since it’s unlikely that your target audience will find you on their own. This means that you’ll need to spend quite some money on ads of all kinds: social media campaigns, audio spots, TV commercials, print ads, etc. The average cost for 1 minute of national TV advertising in the United States is $12000 

The easiest way to do that is by selling digital content and services either through the app itself or on a website that it will generate for you automatically. For example, some apps allow creating online stores and let you sell physical products and digital ones like ebooks and music. This way, both users and co-workers won’t have to leave the app they’re already using to buy something – they’ll only need one click!  Interestingly enough, you can make money off your app, even if it’s free.

Apps may be just what your business needs to draw attention from potential customers worldwide. They allow you to improve user experience and provide users with added value that is more than enough to make them come back for more. Don’t forget that you can always outsource app-building tasks; there are plenty of people around who specialize in this field and will be glad to help you build your next business.

PlatoAi. Web3 Reimagined. Data Intelligence Amplified.
Click here to access.

Source: https://www.aiiottalk.com/future-and-facts-of-apps/

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AI

Future and Facts of Apps That You Need to Know

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Whether it’s Facebook, Whatsapp, or Uber, we can’t imagine our lives without apps anymore. Some people would even say that apps are a must for businesses today. What makes this so popular, and how should you approach app marketing? Let’s find out!

An app is a software designed to work on mobile devices such as smartphones and tablets. They allow users to do many things, from shopping online to playing games while on the go.

“One of the biggest advantages of apps is that they help companies save money by using fewer resources than websites and other offline mediums.” 

Data collected by app stores and statistics show that more and more people prefer using apps over traditional methods of getting information; in fact, 50% of Americans use their phones for research before making purchases, according to one study. But is it all smooth-sailing?

Note the details

As more and more daily tasks become mobile, app makers compete with each other for user attention and time. It’s quite hard to build a perfect app because so many people expect so much from them: we want apps that keep us up to date about the latest news, let us chat with friends and family, give us directions when we’re lost, track our fitness goals and help with shopping online. Providing such features requires a lot of time and money and lots of expertise that not every company has access to. That’s why some experts think that apps might be just a short-lived thing and will die out soon. But this doesn’t mean apps are bad for business!

App usage is still growing. App Annie’s revenue increased by about 70% in 2015 and surpassed $50 billion. The same report shows that there are more than 26 billion downloads every year. So, if you’re thinking of entering the mobile space or taking your existing business online, you should put some serious thought into building an app. Let’s look at how it works and what tools you need to create one yourself.

There are four main steps to creating an app: coming up with an idea, choosing a platform, making the prototype, and testing it. If you want to build an app on your own, it’s best not to start from scratch but to use free or paid tools that come with ready-made templates. Popular choices include the Phonegap building tool, Appcelerator, and Xamarin. However, there are alternatives to these which might be even better for your needs. For example, if you want to save some money, you could use Python instead of C# because the former is free while the latter requires purchasing a license, check RemoteDBA to know more

Interesting Facts about Apps

If you have an app idea but lack the expertise or time needed to create it yourself, you can always hire professional app makers. They will make everything from scratch and help grow your business by meeting set objectives. Prices vary depending on what your app does and how complex it is; we recommend starting with $25000 and going up from there.

The average price for a good design ranges from $5000-8000. Before starting to code the app, you need a special UX/UI designer who can foresee all potential problems and put everything for you. They will develop a detailed plan that will include the actual cost since this part of development is quite expensive, too, especially if you want your app to be original and creative 

If you decide to make an app yourself, it pays off to get some help from assistants or co-workers. You can even hire virtual workers from India or Bangladesh – they are very cheap, have extensive experience in the software industry, and know-how to work remotely, which means it’s easy to coordinate with them. A good developer charged by the hour will cost you about $15-20, while a virtual assistant from Dhaka costs around $3 per hour.

Customers often prefer virtual workers who don’t have time to deal with various issues and processes involved in company administration. Using services like Upwork or Freelancer allows businesses to get rid of this trouble forever!

After getting a functional app, you might want to engage in some advertising since it’s unlikely that your target audience will find you on their own. This means that you’ll need to spend quite some money on ads of all kinds: social media campaigns, audio spots, TV commercials, print ads, etc. The average cost for 1 minute of national TV advertising in the United States is $12000 

The easiest way to do that is by selling digital content and services either through the app itself or on a website that it will generate for you automatically. For example, some apps allow creating online stores and let you sell physical products and digital ones like ebooks and music. This way, both users and co-workers won’t have to leave the app they’re already using to buy something – they’ll only need one click!  Interestingly enough, you can make money off your app, even if it’s free.

Apps may be just what your business needs to draw attention from potential customers worldwide. They allow you to improve user experience and provide users with added value that is more than enough to make them come back for more. Don’t forget that you can always outsource app-building tasks; there are plenty of people around who specialize in this field and will be glad to help you build your next business.

PlatoAi. Web3 Reimagined. Data Intelligence Amplified.
Click here to access.

Source: https://www.aiiottalk.com/future-and-facts-of-apps/

Continue Reading
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