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What is Artificial Intelligence? And Why Should Business Owners Care?

How AI is changing business today and tomorrow:

What is artificial intelligence?When you first think of AI, we know you’re picturing a robotic creature swirling around an office.  And while some robots have entered our lives (thank you Roomba!) most AI we experience is actually not easy to physically “see.”  Artificial intelligence is largely found within algorithms and software that is already making our lives easier, and we haven’t even realized it!  AI is loosely defined. The AI we are experiencing today is a only a glimpse of what is to come.

What is artificial intelligence?

First off, I always like to give some basics because terms like artificial intelligence are so new to our vocabulary.  Artificial intelligence, or AI, is the “simulation of human intelligence processes by machines, especially computer systems.” AI is characterized by having learning capabilities, reasoning skills, and self-correction capabilities.  The systems do this by acquiring information and following a set of rules as to how to use that information.

By now, hopefully, you’re picturing your smartphone or a computer screen more than you’re picturing a giant robot when you think of AI.  AI is already all around us and is already changing how we do business, but there’s still a lot to come.  Here’s a preview of what we’ll see AI do in the workplace:

  1. Automation of Simple Tasks.  Artificial intelligence has already allowed us to simplify simple tasks that are mundane and routine.  If there are set rules or parameters that a program can follow and repeat, AI could be employed to do that task for you.  Things like research for legal discovery on cases, for example, is a great task that is routine within certain rules and can then allow attorneys to focus on the complex parts of a case, rather than just research. Another example of automation is how EnergizeMail’s tool will learn from your habits and automatically file emails based on your unique user habits, saving you precious hours to drive more business instead of filing emails.
  2. Virtual Assistance.  We’re already seeing virtual assistants help us out with simple tasks when we talk to Siri or Alexa.  These programs help us find the nearest gas station or the highest rated restaurant nearby.  These types of programs will only become more relevant, accurate, and helpful as time goes on and the programs get perfected.  Scheduling, reserving meeting rooms, and finding the perfect gifts for clients are tasks that often make up full time positions, and many of these tasks will soon be automated with virtual programs.
  3. Informed Tasks.  Artificial Intelligence utilizes crazy amounts of data and information to make their decisions, which means that the more we incorporate AI tools into our business day, the more educated decisions we’ll be making.
  4. Efficient Solutions.  AI has the ability to incorporate massive amounts of data and organize it in a way that gives you essential information.  So, for example, an IT department would be able to get a comprehensive look at a specific user’s problem and know exactly what is going on before ever heading down to their machine to fix a problem.  The physical back and forth that IT departments know all too well is eliminated, providing efficient solutions and improving efficiency!

This is just scratching the surface of what AI can, and most likely WILL, do in our business environments.  AI will make us more efficient employees and more stimulated employees who are using our expertise and brain capacity to their fullest extent.  We won’t be spending as much time on mundane tasks that waste time and don’t produce results.  Instead, our businesses will be able to focus on growth and truly maximizing our expertise to benefit our clients.  Now, isn’t that a fun thought?!

Machine Learning and Google: Match Made In Heaven

How Will Machine Learning Affect Business?

What were you doing in November 2016? If I were to make a guess, you were probably getting ready for the holidays. It was around that same time Google announced one of the most under-the-radar announcements regarding machine learning.

Google Translation & Machine Learning

On November 22nd, 2016 Google published an articled entitled Zero-Shot Translation with Google’s Multilingual Neural Machine Translation System. Just two months earlier, Google announced Google Translate’s transition from phrase-based translation to a new system called Google Neural Machine Translation (GNMT).

How Will Machine Learning Affect BusinessYou might wonder what’s wrong with phrase-based translation. It’s the same approach you used in freshman Beginner Spanish memorizing phrases in Spanish to hold broken conversations with your classmates. You also probably used phrase-based translation during your spring break trip to the Alps while you awkwardly fumbled through your new English-French dictionary to hit on that one girl at the Louvre.

There’s one problem: phrase-based translation is effective, but clumsy and stilted to use. It doesn’t provide the nuance of language any of us incorporate throughout our everyday conversations. Phrase-based translation doesn’t capture the natural flow of communication used in every language around the world today.

Massive Upgrades In Online Translation!

The GNMT platform serves as a complete end-to-end learning framework. The challenge facing Google is that Google Translate currently translates over 140 billion words every day in 103 languages. With its previous phrase-based translation platform, Google Translate required a suite of network systems to accurately translate between any two languages. This necessity cost Google a significant amount of computation and financial resources. By connecting Google Translate to Google Neural Machine Translation (GNMT), it effectively received massive upgrade in translation horsepower.

Google believed the GNMT system would allow Google Translate to improve translation quality. In initial testing it was obvious the GNMT system’s ability to provide more accurate translation results was significant. This raised another dilemma: how do you scale a neural network as dynamic as GNMT to accommodate 103 unique languages worldwide?

Google elected to extend its previous GNMT system into a single system for language translation. There was no specific change in the existing GNMT system with one exception. Google included an extra “token” connected with the input sentence that allowed the system to select the desired output language for translation. Google also enabled “Zero-Shot Translation,” which occurs when language pairs with no previous inter-translation history in the GNMT system were triggered for translation between the two languages.

As you can see in the graph below, a multilingual GNMT system expands on the previous single GNMT system. In this example, the different language pairs share the same system for translation. This allows the system to transfer “translation knowledge” between language pairs to leverage the full potential of the multilingual model.

Photo Creds: https://1.bp.blogspot.com/-jwgtcgkgG2o/WDSBrwu9jeI/AAAAAAAABbM/2Eobq-N9_nYeAdeH-sB_NZGbhyoSWgReACLcB/s1600/image01.gif

Google was hopeful this zero-shot translation opportunity would be realized. Would the GNMT system be able to translate two languages never before encountered by the system in a translation pair? Google was amazed to learn the GNMT system created reasonable translation results between language pairs in a zero-shot translation scenario.

Google Learning On Its Own

How did the GNMT system know how to translate between languages with no previous experience in its system? It learned. In essence, the GNMT system appeared to created a new language to help translate more effectively… without human influence. The artificial intelligence capabilities inside the neural network of the GNMT system developed an interlingua of sorts to aid in translation accuracy.

Translation, pun intended, the GNMT system seemed to invent an internal language to increase translation efficacy without anyone telling it to in just a few short weeks.

GNMT Google Translate team member Mike Schuster (Google Brain Team), Melvin Johnson (Google Translate), and Nikhil Thorat (Google Brain Team) shared their perspective:

“Within a single group, we see a sentence with the same meaning but from three different languages. This means the network must be encoding something about the semantics of the sentence rather than simply memorizing phrase-to-phrase translations. We interpret this as a sign of existence of an interlingua in the network.” (Google Research Blog)

As of Google’s article published date, the multilingual GNMT system is enabled for all Google Translate users for ten of the 16 launched language pairs. This new approach is leading to better translation results with a simplified framework for helping people around the world understand each other better.

What the success of Google Neural Machine Translation (GNMT) means for neural networks

Does the GNMT system success signal a shift in neural networks? Technology experts have long believed in the power of neural networks to realize the potential of artificial intelligence. Neural networks are built in similar infrastructure of organic, biological brains. Their capacity to reason, deduct, implement, and even react is what drives technology leaders to explore new challenges to solve.

Neural networks, also known as artificial neural networks (ANN), thrive on recognizing patterns in data. IBM supercomputer Watson is already recognizing patterns in medical data, weather forecasts, legal matters, and education systems. I believe neural networks have the power to change every industry through artificial intelligence. The ability to think and respond in a human-like manner at an exceptionally high level of computation is opening new frontiers and solving countless problems.

What Does This Mean For Everyday Life?

In our immediate context, what does the Google Neural Machine Translation system’s success mean for your everyday life? It means our ever-diversifying world will better accommodate the melting pot of languages in every major city. I see a future where language groups can communicate more easily than ever. AI headsets connected wirelessly with Google Translate will allow us to automatically hear and understand any foreign language in our native language. Businesses will span language barriers and conduct business more efficiently than ever because neural networks will make translation easier than any other time.

The way the world communicates is changing because of Google Translate. Will we need to learn new languages? Maybe not. The potential to overcome millennia of miscommunication and communication barriers cannot be overstated. With the right technology, Google is committed to making sure this opportunity isn’t lost in translation.

 

Learn more from NEO about how machine learning, natural language processing, and other emerging technologies impact business on our main website.

What Is Data Warehousing and Why It Matters

What Is Data Warehousing
Let’s say your company wanted to collect and store all the data generated by customer activity and everyday business operations. Where would you store your data? You probably want to store it on a computer in one of your offices. On-site data storage is fairly secure… but is on-site data storage up for the task?

Think of all the big data that could be collected by your company: transaction details, call information, customer service details, purchase orders, shipping information, CRM task management, and the list goes on and on. The sheer volume of data generated by a business with a seven-figure annual revenue is more than a single computer can store on site. If you’re wanting to collect and store data for your business, I recommend looking at data warehousing.

 

Data Warehousing Basics

Data warehousing (DW or DWH for short) is “a technology that aggregates structured data from one or more sources so that it can be compared and analyzed for greater business intelligence.” It’s worth clarifying that data warehousing is not intended for immediate data recall, like a standard operational database.

Data warehouses are designed to collect and store massive amounts of data for long-term structure and access. Think of data warehousing like renting a storage unit at Public Storage or SmartStop. You probably don’t have your storage unit as organized as you like, but it’s safe, secure, and there when you need to pull out something valuable.

Data warehousing essentially gives your business all the storage space it needs to aggregate data from any relevant source. Why does this matter? Is data warehousing that important to your business? It may not seem like a mountain of unsorted data is important now, but I promise, you will be thankful for your stored data in the coming years.

What Does Data Warehousing Allow Your Business To Do?

The best decisions in business are based on empirical evidence, such as data contained in client surveys, purchase trends, year-to-date cash flow markers, and more. Data warehousing gives your company the necessary fuel to feed a data aggregator, such as a CRM algorithm, to identify money-saving or sales-generating trends in the future. Want to know what’s your most profitable week of business each year over the past ten years? Transaction and customer activity recorded and stored in your data warehouse can give you unprecedented insight to start answering that question.

Businesses are just starting to scratch the surface of data’s reach and potential. At the heart of implementing stored data is business intelligence. CIO defines business intelligence as the following:

Business intelligence, or BI, is an umbrella term that refers to a variety of software applications used to analyze an organization’s raw data. BI as a discipline is made up of several related activities, including data mining, online analytical processing, querying and reporting.”

Business intelligence is empowering businesses with exact insight to ignite intentional growth into the future. When future economic trends start affecting entire industries, businesses who leverage their stored data for business action will have an immediate competitive advantage. What does this mean for your business?

Imagine having the ability to mine any volume of data for lost transactions. You could also extract any criteria of business activity to capitalize on new opportunities. What if your business could open up a new market sector just by using previously stored data? The right amount of data can also give you a reliable 360-degree perspective of your business and all personnel making an impact on your success.

Data integration allows you to build complete profiles for hyper-accurate marketing campaigns. Reducing ad waste will allow your sales and marketing personnel to start with optimal marketing-qualified leads. This means you’re not spending time talking with people who are not good fits for your company’s buyer profile. Better leads means a higher likelihood of maximizing sales from the first conversation.

Business intelligence curated from stored data in your data warehouse allows your company to understand how and where your staff spends their time. How often does a certain client call each month? How many emails does it take for the average prospect to convert their interest into confirmed sales? The ability to know how much each client (and each of your team members) is costing you provides clear-cut data to make the best business decision. Wouldn’t you rather know which team members are pulling their weight and which are not?

Data Ready To Use

All of these benefits are possible simply because you have the data at your disposal. No data warehouse, no opportunity to leverage data to increase dollars. If your business is not using data to make intelligent, concrete decisions, you will be left assuming what you’re doing is working well enough.

NEO can consolidate, integrate, and organize your enterprise’s data in a meaningful way with custom database warehousing and architecture solutions. Database architecture solutions mean we can build the right data warehouse for you with the right criteria to tag the appropriate data as it comes into storage. We work with a variety of data solutions, such as: SQL, MySQL, noSQL NEO4J, Big Data Solutions (example: Hadoop), and more.

We work with you and your team to help you know how to access your data from your system. If sorting through an entire data warehouse sounds daunting, we also have self-service business intelligence (BI) solutions to give you a simpler way to search your data.

The first step is starting a conversation about data collection and storage. We help you answer big questions, such as the following and more:

  • “How much data do I need to store for my business?”
  • “How frequently do I need to access my data warehouse?”
  • “How secure is my business data warehouse?”

Click here to schedule your initial consultation with our NEO team. We are a Denver business intelligence firm built to help your business build a profitable relationship with data. We can help you collect data intentionally to power intelligent business growth.

Artificial Intelligence Is Literally Changing Lives

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Artificial Intelligence: I know I mention this as a topic and your thought immediately goes to the movie Terminator: droids that are built to look, act, and sound like humans who are intent on taking over the world. Don’t worry, droids taking over the world probably won’t happen any time soon.

What is closer than we might realize is the integration of Artificial Intelligence (AI) into our everyday world.

How Artificial Intelligence Will Change The FutureThe concept has been growing for years, but it’s never been closer to reality than today. Artificial Intelligence is finally living up to its potential. It’d be helpful to know what we’re talking about when it comes to Artificial Intelligence.

As silly as it may sound, ‘artificial’ may not be as clearly understood as it seems, and also, ‘intelligence’ may have different levels of expectation from each of us. The human brain as the home of natural intelligence is, of course, the birthplace of artificial intelligence. The human brain experiences a cacophony of electrical activity that translates into motor movement, spoken and nonverbal communication, situational processing, and at the very basic level, our ‘fight or flight’ response.

A Story of a Monkey and AI Changing Lives

Dr. Miguel Nicolelis, Professor of Neuroscience at Duke University (Durham, NC), became fascinated with ‘brain storms’: electrical activity caused by neurons firing between the more than 100 million cells in the human brain. Dr. Nicolelis’ research recorded this neural activity and decoded the neurons as a sort of alphabet to communicate with extensions and devices outside the body.

Dr. Nicolelis and his team developed a Brain Machine Interface from 2000 to 2001 with a multi-channel sensor system to receive the electrical communication from the brain. The receptor system then processed the electrical signals as part of real-time analysis of brain activity. The sensors are designed to specifically look for any signals that are connected to motor movement: raising an arm, shifting a foot, flexing fingers, or even standing up from a seated position.

Any motor movement information was then sent through a telemetry processor to a 3D artificial limb, such as a robotic arm. But the question remained, how well did the translation of the motor movement work, from the brain’s electrical impulse to the robotic arm? Dr. Nicolelis’ team started experimenting with a rhesus monkey named Aurora in early 2003. The research team monitored and recorded Aurora’s brain activity while playing a simple computer game with a joystick. If Aurora completed a basic challenge in the game, she received an automated drip of Brazilian orange juice as her reward.

Aurora’s ‘brain storms’ were uploaded to a robotic arm using the Brain Machine Interface so the computer and a robotic arm could begin learning Aurora’s impulse and motions to play the same game. When Dr. Nicolelis’ research team switched to the Brain Machine Interface after thirty days, Aurora was able to simply think of the direction to move the sensor in the computer game and the robotic arm responded based on her brain activity.

Two Monkeys Changing The World

In a similar situation, researchers from the University of Pittsburgh and Carnegie Mellon University experimented with two macaques monkeys in using robotic arms to eventually establish brain control over an artificial appendage. The scientists identified 100 motor neurons that a computer analyzed in their electrical activity and translated the neural activity into an electronic command to move the robotic arm. The arms were mounted flush with the macaques’ left shoulders and the computer initially helped the monkeys move the robotic arm to help establish motion control.

As the monkeys learned to adopt the movements, the research team noticed an adaptation of movement that could not be anticipated in virtual environments. The testing results show the brain’s amazing ability to adopt, adjust, and use a prosthetic appendage based solely on the brain’s motor activity fired in a specific area of the cortex. Dr. John F. Kalaska, neuroscientist at the University of Montreal, after seeing the macaques’ progress, noted that, “[Brain-activated prosthetic limb adoption] would allow patients with severe motor deficits to interact and communicate with the world not only by the moment-to-moment control of the motion of robotic devices, but also in a more natural and intuitive manner that reflects their overall goals, needs and preferences.”

So, if the brain is capable of creating the right type of data to control a prosthetic limb, could the brain control more than one prosthetic limb at a time? Dr. Nicolelis and his research team posed that same question while continuing to study Aurora’s ‘brain storms’. The difference is that Aurora was controlling a single robotic arm over 7,000 miles away at Kyoto University in the Kyoto Prefecture of Japan. The control signal between Aurora’s brain and the robotic arm at Kyoto University was registered at 20 milliseconds faster than the brain signal between her brain and other muscles in her body.

The Duke University research team added a second monkey to their experiment… and a second robotic arm for both monkeys. Implants in the monkeys’ brains tracked and translated between 374 to 497 motor-controlling neurons to send the appropriate signal to the robotic arms. The two rhesus monkeys have successfully controlled both arms at the same time using a new and improved bimanual brain-interface machine. The results are promising because, of course, the ultimate goal isn’t just to allow perfectly functional monkeys to control robotic arms. The hope is to empower paraplegics and amputees with the brain-controlled capabilities to enjoy life without limits.

What Does This Mean For Humans?

To put this simply, this research proves that our brain has the ability to form new pathways. How does this translate into our daily lives? It means that while you are working there is the potential for your brain to be controlling a robot at home cleaning your house. It takes the concept of multitasking to a whole new level.

Think about the possible implications!

But, how can artificial intelligence be applied for quadriplegics? What if no neural activity is registering any motor control inside a human body? The same advances in brain-machine interface technology are now allowing monkeys to control a robotic wheelchair simply by thinking. Dr. Nicolelis and his team monitored the brain activity of two rhesus monkeys that were trained to maneuver a wheelchair just by watching it move. The monkeys transitioned to using their brains’ neuron signals to navigate a two-meter path across the room to retrieve grapes from a dispenser. The experiment required careful insertion of intracranial implants to register the monkeys’ neural activity for far superior motor control of the wheelchair.

The data received from monitoring the two monkeys’ brain activity while telematically controlling the wheelchair is the same type of data that may be used in the future to improve the livelihood of severely disabled people. People suffering from Amyotrophic Lateral Sclerosis (ALS), Parkinson’s, or any number of motor neuron diseases, now have hope of controlling their livelihood. Dr. Nicolelis and his team have now started implementing the discoveries and data tracking capabilities of their brain-machine interfaces into human experimentation.

This article is an excerpt from NEO founder Jesse Morris’ new book Data and the World of Today: The Reality of Today that will Impact your Business Tomorrow. Purchase your copy via Amazon.com.