Archives for October 2018

Since you just passed your online defensive driving course, you might be in the market for a new car. With so many options to choose from, getting overwhelmed is easy. So, why not make the decision process a little simpler by choosing a car based on what your favorite celebrity is driving?

Whether you’re an action movie fan or a rom com aficionado who knows the best tips for driving in New York, chances are you have a favorite celebrity. After all, they are the perfect role models to emulate. Below, you’ll find a list of your – potentially – favorite celebrities and the incredibly expensive car they drive.

Dwayne “The Rock” Johnson – 2018 Ford Mustang

Dwayne “The Rock” Johnson drives a 2018 Ford Mustang. Who would have guessed one of the strongest actors in Hollywood was a fan of muscle cars? Whenever he’s not taming giant gorillas in movies or hanging from a skyscraper, Johnson is cruising the hills of Hollywood in his black, Ford Mustang.

Meryl Streep – Toyota Prius with Hybrid Engine

Often regarded as the manifestation of regalness, Meryl Streep drives a Toyota Prius with a Hybrid Engine. It’s a humble car choice for someone of her status. As a known advocate, the only thing more important to her than acting is saving the environment. 

Tom Hardy – Audi R8

From his recent film as the villain Venom, you might not have guessed Tom Hardy would drive an Audi R8. However, the evil Hollywood heart throb has a fascination with Italian sports cars. He’s also known to drive an array of other cars from his collection of unique, expensive vehicles.

Cate Blanchett – Another Toyota Prius

Cate Blanchett has made appearances in some big films this year. Such as Thor: Ragnarok, Ocean’s Eight, and The House with a Clock on its Wall. But, her massive fandom doesn’t convince her to drive anything other than a Toyota Prius. Making good movies is just as good as making good environmental decisions. 

Bradley Cooper – Mercedes G55

Bradley Cooper is everyone’s favorite hunky Hollywood crush. When he’s not playing a rugged, conflicted cowboy, he’s strutting his comedic chops. You can catch him driving around town in his Mercedes G55, which is also known as Bradley Cooper of cars.

Viola Davis – Mercedes Benz

Viola Davis is the star of the hit show How to Get Away with Murder. Among other notable roles, she’s fan favorite of murder mystery shows. This explains why she drives a Mercedes Benz. It’s a sturdy, luxury vehicles for someone with a sturdy luxurious career.

Robert De Niro – Audi RS7

You might have expected Robert De Niro to drive a taxi, but he actually drives an Audi RS7 – among other vehicles in his collection. He’s a known car collector, but oddly enough left the taxi driving behind him.

Emma Stone – Another Audi

Emma Stone drives an Audi but based on her driving record could end soon. Driving an Audi could invite reckless driving because of their high velocity, but that’s a small risk Stone is taking.

Chris Hemsworth – Cadillac Escalade

Known for his beloved role as Thor in the Thor film franchise, Chris Hemsworth would drive something equivalent to his burly build. The Cadillac Escalade is his choice for driving him and his family around town. Its large size is an allegory for his large muscles. 

Amy Adams – Yet Another Audi  

It turns out that a lot of celebrities drive an Audi. Amy Adams is no different either. Whenever you aren’t seeing her in the movies, you can catch Adams in her Audi. If she doesn’t like the car for its speed, she likes it for the A alliteration.

 

Machine learning is not an unheard concept for most of us, after all it’s 2018 and popular culture alone has theoried a plethora of post-apocalyptic timelines where machine learning runs amuck. The more pedestrian (though still exciting) reality is the rapidly expanding and unique applications of large-scale data analytics to create dynamic and predictive computer models.

 

A pioneering process of analysing and automating data that gives computer systems the ability to ‘learn’. Using complex algorithms that frequently learn from raw data and information, machine learning gives computers the ability to discover hidden insights without being specifically programmed on where to find them. The massive data sets used for machine learning make it possible for computers to extract both patterns and anomalies from the torrents of information. It’s an evolution of Artificial intelligence practices such as pattern recognition and computational learning theory, machine learning allows programmes to make faster, more accurate data-driven decisions.

Okay, so it’s making computer processes more efficient, reliable and cost effective, this becomes a recipe for explosive growth as it translates into a number of tangible bottom line benefits for any business that interfaces with customers (which is pretty much all of them). The advent of machine learning technology is driving innovation in every sector and will only continue to grow in popularity as it progresses. Big brands have already bought into the machine learning era decades ago when it was fledgling, the potential was always there for data driven artificial intelligence to offer their customers an optimal experience. Apple use machine learning for their voice recognition system, Siri, to imitate human interaction. Facebook use the technology to tag individuals in photos. Google Maps analyses the traffic speed using location data from smartphones. PayPal uses machine learning algorithms to combat fraud. Amazon gets you to spend more money by showing you more products it knows you want to buy based on your history because it’s machine learning algorithms have learnt a lot about the average joe over the last 2 decades.

In the credit industry specifically, brands like Wonga use a business model where machine learning plays an integral role in assessing customer risk and approving loans. So far, it has mainly been used for determining the lending risks of customers based on their income and credit history, but there is much more potential to still be tapped. Machine learning allows credit companies to offer a more enhanced customer experience in a number of ways:

1. Call Reason Predictions:

Call reason predictions are a new and intuitive way for machine learning to make a huge impact on the credit industry. The number of customer calls being made on a daily basis is always increasing, and as a result the number of calls being routed to incorrect departments is an increasing issue. Customers are also experiencing longer wait times than ever, leading to an increase in call drop-offs and unsatisfied customers. Machine learning can help ease this issue by predicting the reason for a customers’ call based on the time of day the call is being made and other variables. This allows the call to be routed directly to the correct department for that specific customers’ needs, resulting in shorter calls and happier customers.

1. Chat Bots:

Machine learning can also be used to assist customer without them having to pick up the phone, with the rise of chat bots and conversational interfaces. Chat bots are virtual assistants that are built using natural language processing engines combined with credit specific customer interactions. Allowing customers to get information and interaction quickly and easily will improve service levels and offer a unique edge over other companies that require their customers to get in touch using traditional methods. As well as improving the customer experience, these virtual assistants save valuable work force time, allowing businesses to save money and have their teams focus their time on other aspects of the business.

1. Fraud Detection:

With the combination of computing power, the internet and an increasing amount of valuable and confidential data being stored online, the security risk to data is higher than ever before. Previously, financial fraud detection systems were heavily dependent on complex and robust rules. Whilst more recent fraud detection goes further than just following a checklist of risk factors, it can actively learn and calibrate to detect new potential security threats. Machine learning systems can detect anomalies in online activities and behaviours and flag them for security teams to investigate further.

1. Product Sales:

Machine learning is a powerful tool for developing more detailed insights into customers and potential sales prospects. Drawing on a wide range of available data, marketers and sales staff are given much more to work with than they have ever had in the past. Customers can be more accurately segmented according to their profiles and probable needs, offering new opportunities for up-selling and cross-selling. This in turn improves the customer experience by offering them the exact products that are relevant to their needs.

1. Collections:

Currently some customers have very negative experiences from credit companies due to being contacted by their collections teams unnecessarily. Machine learning can help ease this issue by learning and predicting which borrowers that go into arrears are more able to resolve their issues without contact or support from the credit company. Not only will this improve the customer experience by avoiding unnecessary hassle, it will also have an impact on reducing the cost and time of collections teams.

The credit industry has long had access to an enormous volume of accurate historical records and personal data, making it the perfectly suited for machine learning optimisation. Expect to see a huge increase in the amount of machine learning applications being applied within the industry in the near future, indeed expect to also see it become the mainstream foundation for the marketing and customer service strategies of even small business owners across the web. As the availability of user information nears 100% (do you know anyone who doesn’t use a smartphone now?) the investment into this sector will continue to grow as countless applications and valuable, market dominating insights about our customers await realisation.

 

If you are involved in a personal injury case in Houston, figuring out the proper actions to take can become complicated and overwhelming. If you don’t know how to plead your side of the story, the case can become a nightmare; this is especially true because there is a possibility that you will end up getting way less than you are entitled to for your injuries.

The best way to get all that you deserve is to hire a Houston personal injury and refinery accident attorney. If you do choose to go it alone, however, there are some behaviors and dos and don’ts that are essential to get the most from the incident.

The reality is that only about 97% of all personal injury cases ever see a courtroom. Most are settled during the negotiation phase of the trial but be careful of what you agree to and sign. Once you accept a settlement offer and sign it, you absolve the insurance company from paying for anything else that should arise. So, that is why it is so critical to know what your case is worth before you end up leaving money on the table and walking away with way less than you should.

Don’t say anything

When you are in negotiation, the worst thing that you can do is to throw out a figure for settlement. Once you put a price on the table, an adjuster will work overtime to whittle you down. It is best to have the adjuster suggest a price first.

If you determine the price first, the adjuster knows how much you will take, and it might be far less than what they had already decided was their maximum. It is best not to put a price in your demand letter, let them do the work and work hard to decrease, instead of trying to hold the insurance from reducing the number you’ve thrown out.

Know what you will settle for before you enter into a negotiation

Before you go into the negotiation phase, know what you will and won’t accept for your injuries. Economic damages are going to be difficult to deny for the adjuster. So, likely there isn’t going to be any argument about what your economic damages are worth.

When it comes to non-economic damages, however, things can go awry pretty quickly. Since non-economic damages seek to compensate you for the experiences you had related to the accident, they are less concrete and don’t come with a set of physical documents.

It is best to understand what your injuries are worth by working with a personal injury lawyer to know how to calculate what your non-economic damages are worth. If you don’t know add up the cost on your own, then you won’t know if you are getting all that you deserve or even just the minimum you need to continue paying bills.

Your injury lawyer in Houston takes a personalized approach that is catered to your individual needs. The attorney can use either the per diem method or the multiplier method to come up with a reasonable starting point for your non-economic damages. These strategies help you to feel confident about what you are willing to accept and what is unacceptable before you even approach the table.

Start high

It is always best to ask for more than you are willing to take for a settlement. If you start at the least you will accept, then you are not going to have much room for negotiation. Estimate high and make the insurance company work to whittle you down instead of the other way around.

You have to sell yourself

During the negotiation phase, you have to strategically haggle with the insurance company. It is important to prepare by learning certain tactics like walking away, stalemating, and other forms of haggling; these strategies will work in your favor. The insurance company does not want to have to waste the resources taking your case to court so play hardball to let them know that you can’t be pushed around.

Never show your cards

No matter where you are in the negotiation phase, never reveal what your bottom line is. If you do, that is all that you are going to get and probably less. It is imperative never to let the insurance company know what you will settle for or you will end up receiving less than you deserve.

It is an excellent idea to hire a Houston personal injury lawyer to make sure that you aren’t  missing out on any money. If you aren’t an expert at negotiations, you should either become one or make sure to have someone there with you who already is.