Tinman Kinetics

Understanding the Basics of Node JS

Jade Kim — Mon, 30 Mar 2020 20:40:23 GMT

Node JS is a JavaScript runtime environment, easy to think of as JavaScript on the server. Node js uses V8 engine and includes some additional modules that give you more browser features and JavaScript functions.

The role of node js in web development is …

To run server which is creating a server and listening to incoming requests.
To handle business logic. For instance, handle requests, validate input and connect to database.
To return responses such as HTML, JSON, XML or files to client.

How to create a node.js server

Import http module: const http = require('http');
Create a server: const server = http.createServer((req, res) => { });
Execute and listen to the server: server.listen(3000);

const http = require('http');

const server = http.createServer((req, res) => {
    console.log(req);
});

server.listen(3000);

To make a request to the server, open a browser and navigate to http://localhost:3000. You will see the req in the console!

To start the Node.js server: node fileName ex) node index.js
To quit the running Node.js server: CTRL + C

Requests and Responses

: Below code is a very basic example to handle requests and responses for understanding the concepts.

const server = http.createServer((req, res) => {

    // To see requests, 
    console.log("URL: "+req.url)
    console.log("METHOD: "+req.method)
    console.log(req.headers);
    
    // To send responses, 
    res.write(`
        
            Hi from NODE JS server!
        `
    );
    res.end();
});

How Node JS works

- Asynchronous and Event Loop

Node JS is non-blocking code or asynchronous architecture by default, which a single thread is handling multiple requests. In contrast, Other frameworks or languages such as ASP.NET, Flask and Ruby are blocking code or synchronous architecture, which one thread will handle only one request at a time.

Let’s say there are request A and request B to be handled in our list in order. First, our Node JS thread will serve the request A. If request A needs to query a database, the thread doesn’t have to wait for the database to return the data. While the database is executing the query, the thread will serve the next one - request B.

When the database is ready to return the result for request A, it pushes a message in Event Queue. Node monitors Event Queue continuously in the background. When an event is found in Event Queue, the thread will take the event out and process it. Then Node will check if Event Queue is empty constantly to handle next Event Callbacks. This loop process is called Event Loop including Timers, Pending Callbacks, Poll, Check, Close Callbacks.

Node JS has an ongoing Event Loop as long as there are listeners. If you create a server, it always creates a listener. Therefore, Node JS server will never stop unless you unregister by using process.exit.

Because of these features, node appications are ...

Faster response time
Agile development
Data-intensive apps
Real-time apps

WHAT IS DIGITAL TRANSFORMATION? IT’S EMBRACING CHANGE

Frank Trevino — Sat, 01 Feb 2020 16:36:32 GMT

First of all, digital transformation is not just about technology. That is the first thing that comes to mind when people think about digital transformation and becoming “digital”. This thinking usually includes what’s the new and latest gadgets that will automatically and magically transform a company into something better.

But the reality is that digital transformation is really about redefining your strategy and cultural mindset or an easy way to say this is, it’s about embracing change and this change starts with understanding where an organization is within its digital transformation maturity model. This “change” approach is best explained through the digital transformation pyramid framework.

Like any pyramid, it starts with the foundation and this foundation is about data-driven capabilities. We know that every person creates data and this data is in the form of selfies, videos, blogs, text messages, etc. Well, the same applies to organizations. Organizations create not just data but lots of data. But the goal is how do we use this data to create value or as I like to say, how do we turn data into digital assets. An asset that brings intrinsic value that can be financial, emotional or intellectual. These data-driven capabilities that lay the foundation to digital transformation include People, Product, Process and Technology. Each one alone limits an organization, but all together in orchestration, then the true value of data transforms an organization, hence the term digital transformation. It is important also to understand that as we look at each part that there are always two-sides to each one of these data-driven capabilities. One side is internal facing to an organization, as to embrace change within the organization. The other side is public facing, which includes customers, investors, enthusiasts and the general public. I always recommend the first step in digital transformation should start internally within an organization because only successful change internally can produce the right results externally.

Digital Transformation is about

PEOPLE

PROCESS

PRODUCT

TECHNOLOGY

People

The key to any organization is people. Without the right people, any organization will fail. Digital Transformation takes a look at the existing personnel, their roles and skill sets.

First, we must assess the maturity level of personnel within the organization. Do they currently possess the proper experience and knowledge to execute digital transformation initiatives? Do they require more training, can they be trained, or should new personnel be brought in to achieve the set goals? Part of this approach with personnel is also understanding throughout this process is the cultural shift that takes place when an organization becomes digital. The first question seems to be, am I going to lose my job? There are many methods to help address these expected challenges during a cultural shift with the main approach to be proactive and not reactive.

The other side with people becomes the external component in digital transformation and this usually is associated with the customer. As organizations embrace digital transformation, this same approach internally must also be applied externally. This is really about understanding the customer, how they use your product and how they will be affected by digital transformation changes such as integrating new technology. Traditionally, these changes are positive as customers tend to embrace positive change, but time must still be taken to understand its impacts and how to benefit from these changes.

Process

Processes change as often as organizations and customers change. Today, the most talked about processes include lean, agile and more traditional methods such as SixSigma. As with change management, a new strategy means adjusting, creating, developing and initiating process to create better efficiencies.

Internally with digital transformation, it is applying the same approach with the new digital strategy and asking the questions, what changes in process are needed such as improving an old process or creating new ones to adapt to the tasks at hand. Process changes should start out small but gradually expand across departments to fully embrace the new digital strategy.

Externally, it is about process with stakeholders outside the organization such as suppliers, vendors, partners and customers. This could be a vendor management solution that requires new processes and will involve training your vendors on how to use but it also means feedback from your stakeholders on the ease of use, efficiency and purpose of the system. Any process change should always include a feedback loop to continually improve for all stakeholders

Product

You are only as good as your product and his holds true for any successful organization. Digital transformation definitely embraces change with product in mind. Customers buy your product because it helps solve a problem, but today there are a lot of organizations that are making similar products to help solve that same problem, so how do you stand out? This usually involves improving your product to connect with your changing customers. Digital transformation helps improve your product, if done properly.

Internally like process, it is understanding what the product does, how it’s built, time to market, how difficult to make upgrades or changes, the resources needed, all in order to make the proper change to align with the digital strategy.

Externally, its understanding how changes in product will be received by the market, not just customers. It also takes a deeper look at your product against competitors to properly evaluate value proposition and positioning.

Technology

We sometimes feel like we are a little kid in the candy store when it comes to new technology. It’s cool, fun, new, exciting and believe it will take an organization to new heights. As I said before, it’s like magic. This is where many people fall into the trap of SOS or Shiny Object Syndrome. We see a new shiny object and our eyes and wallets are wide open. This is especially true after returning from events such as CES (Consumer Electronics Show) in Las Vegas or Mobile World Congress in Barcelona.

In digital transformation, we need to first step back from any new technology and internally evaluate what existing technology is in place within an organization. The key here is understanding what technology is in place and more importantly how much time, effort and resources are already vested in that technology. The second part of this is to ask if we are bringing in new technology, will it be a substitute, or will it replace existing technology. The last thing anyone wants to do is bring in new technology to replace existing when that existing technology ROI is still not in reach.

Externally, it is really understanding how new technology will bring innovation to the organization. This innovation could be within the organization or it could be within existing product or even create a new product. Also, will this technology give the product a competitive advantage, meet a new market need, or just be trendy. Technology is a big investment, so thorough evaluation must be considered before making any decisions.

It’s all Connected. The Cultural Mindset Change.

We all realize that alone, each one of these data-driven capabilities bring limited value when understanding the digital challenges organizations face, but together and aligned by strategy and framework, then it’s a different story. But we still need to take this one set further. All of these data-driven capabilities require a progressive approach to be successful. Needed is the cultural mindset change to continually promote adoption, reduce uncertainty and foster innovation, all leading to a better organization and better customer experience.

5G, Artificial Intelligence, and Space – It’s All Connected

Frank Trevino — Mon, 13 Jan 2020 19:11:46 GMT

The 2010 decade marked a dramatic change in innovation and the evolution of progress in several industries. Starting with the adage that the government can only access space but now look at the private space industry today; that AI is just science fiction and now it’s turning science fiction into reality; and finally, from our early stages of 1G to almost seamless data access with 5G today. While each one was on its path, today they are converging as one to bring about positive disruptive change.

Welcome to 2020. As technology leaders, we shouldn’t look at 5G as the only answer to accelerating ICT innovation. 5G is part of the equation. 5G is driving AI by allowing higher bandwidth, lower latency, and increased capacity. 5G is also the latest business case for a new generation of global constellation space satellites to support the growing IoT sector, even with idea of data centers in space. AI is leading the ability to self-diagnose, self-heal and self-orchestrate 5G technologies such as virtualized networks to lower costs. AI also plays a large role in reducing risk to access space through autonomous and reusability management thus bringing down the cost to access space. As access to space improves, space R&D brings innovation for the next generation of wireless communications beyond 5G while working on better materials to improve computing power to drive the next-generation AI.

By combining all three sectors, we as a society can better tackle the challenges in medicine, such as beating cancer; in science, such as reversing climate change; and in technology to build sustainable cities, all which will benefit humanity. It’s all connected.

How to install Mongo in macOS/Linux with Homebrew

Jade Kim — Wed, 08 Jan 2020 19:57:22 GMT

Install Mongo in macOS/Linux

1. Install Homebrew

Homebrew is a Package Manager for macOS/Linux.
Go to https://brew.sh/ and find a command for installing Homebrew and run in your Terminal prompt.

/usr/bin/ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)”

(optional) Install node js with brew by the line below if you need: brew install node

2. Setup a custom Homebrew tap and install mongo

Add a custom tap: brew tap mongodb/brew
And install mongo: brew install mongodb-community

Homebrew will create the conf file and paths below as defaults.

the configuration file: /usr/local/etc/mongod.conf
the log directory path: /usr/local/var/log/mongodb
the data directory path: /usr/local/var/mongodb

To run mongod as a service, brew services start mongodb-community.
To stop the server, brew services stop mongodb-community.

It uses the default conf file and paths for mongodb and the log.

To verify that MongoDB has started successfully: ps aux | grep -v grep | grep mongod

To connect and use MongoDB, open a new Terminal and run mongo. MongoDB shell is now up and running!

Set mongo db and log path manually

- Troubleshooting errors for beginners and macOS Catalina

If you get the exception similar to below, you will need to create a directory for mongo data with following command: sudo mkdir -p /data/db

exception in initAndListen: NonExistentPath: Data directory /data/db not found., terminating

BUT you might get the another error, mkdir: /data/db: Read-only file system. That might be because you are using macOS Catalina.

Starting with macOS 10.15 Catalina, Apple restricts access to the MongoDB default data directory of /data/db. On macOS 10.15 Catalina, you must use a different data directory, such as /usr/local/var/mongodb.
https://support.apple.com/en-us/HT210650

Since you cannot create directories in root system, create the db directory with sudo mkdir -p /Users/YOUR_USER_NAME/data/db.

Tip: Find out your username by running this command: whoami

And create the log directory: sudo mkdir -p /Users/jadekim/data/log/db

Then run mongod manually by setting up the db and log path with following command.

mongod --dbpath=/Users/jadekim/data/db --logpath=/Users/jadekim/data/log/db/mongo.log

But you might still get another error.

exception in initAndListen: IllegalOperation: Attempted to create a lock file on a read-only directory: /Users/jadekim/data/db, terminating

We need to set permissions for the data and log directories: sudo chown -Rv YOUR_USER_NAME /Users/YOUR_USER_NAME/data/db

In my case: sudo chown -Rv jadekim /Users/jadekim/data/db

Finally, you can run mongod successfully!

mongod --dbpath=/Users/jadekim/data/db --logpath=/Users/jadekim/data/log/db/mongo.log

Open a new Terminal and run mongo.

https://docs.mongodb.com/manual/tutorial/install-mongodb-on-os-x/#install

Frank Trevino - Keynote Speaker on AI at B2B Marketing Leadership Forum 2019

Frank Trevino — Fri, 23 Aug 2019 21:54:00 GMT

Singapore, August 22, 2019

Frank Trevino closed the B2B Marketing Leaders Forum as a Keynote Speaker on AI and its impact on business and marketing. Mr Trevino highlighted the AI journey for marketers with an overview of AI Basics, AI Framework, AI Today and AI Tomorrow. His demo of AI in action with the six AI tools was a great example of AI in the marketplace.

“The goal is to turn Data into Digital Assets” – CMO, Frank Trevino

Mr Trevino stressed the need to always have the human element through company-wide communication and a cultural shift toward creating the digital mentality needed with organizations as they go down the road of digital transformation and AI. He also discussed improvements in cloud storage, computing power and 5G that are making AI possible today and stated, “5G is the rocket fuel for AI.”

Mr. Trevino added that the next step in AI within the B2B market is the immersive experience. He noted that while AI, within B2B, is still in its early stages, we as marketers will learn how to take proven B2C AI solutions and pivot into the B2B market.

He mentioned chatbots, voice analysis and natural language generation of content are already playing a significant role but the future lies within new media approaches using virtual reality, augmented reality and mixed reality.
He added the biggest challenge B2B Marketers face is Progressive Change, balancing too much change stemming from technology, less change wanted by management and constant change needed to connect with ever-changing customers.

He continues,”the three greatest areas AI impacts marketing are knowledge, predictive and immersion.”

In closing, Mr. Trevino stated, instead of telling our brand story, how do we invite our customer into our brand through an immersive experience. This includes us learning how to find new ways to use technology and media to create a greater connection with our audience. “At Exodus Space, we are using virtual reality to allow our investors and potential customers to experience the value of our spaceplane before we have even built it.”

Mr. Trevino added that he will participate as a speaker in the B2B Marketing Leadership Forum in Sydney Australia in May 2020.

Customers, Programs, Partners, & Charities

Justin Williams — Mon, 11 Feb 2019 17:17:07 GMT

We can't talk about everything we do here at Tinman Kinetics, but when we can, we love to talk about some of the incredible solutions, customers, programs, partners, and charities who are just as passionate as we are about pioneering human-centric technology in order to make a lasting impact.

Schedule some time with us to dive into the details and watch this space for updates!

New Security Reality - An AI Defense for Weaponized AI

Justin Williams — Mon, 21 Jan 2019 16:00:00 GMT

Truth is ancient though it seems an upstart.
-Elizabethan Master George Silver, Gentleman

George Silver, author of the "Paradoxes of Defence" in 1599, was one of the last, classical Masters of London, what we would think of today as the quintessential knight in shining armor. He wrote Paradoxes because technology was shifting and with it, he saw everyone collectively lose their minds and throw out everything they knew.

And, yes, OK, he was also a little cranky about the technology change itself - specifically the Italian rapier which was accompanied with a fighting style that, applied correctly, spread far slower than the weapon itself.

Illustration from "Paradoxes of Defence", George Silver, 1599

Safe to say, technology has marched on a lot since then, but Silver still has wisdom to impart today. Cyber security has one of the fastest technology paces because it is an arms race whose defense is largely in the hands of all of us, independently. That means from big enterprise companies to small businesses, we ignore it at our own peril. If you have so much as a static website, or heaven help you, a database online, then the modern highwaymen are already poking at your defenses.

Seriously, it takes about 5 minutes. That's because online attacks were the first to fully embrace automation. Automation is the first stage of maturity when it comes to machine learning and AI, but the next wave already in use in some dark corners of the web have brought something far more dangerous.

The four grounds or principals of that true fight at all manner of weapons are these four:

Judgment

Distance

Time

Place
-George Silver

Silver broke down defense for us into four universal truths followed by a long list of specific strategies related to the tools used. Let's take a look at how to apply some of that ancient knowledge to some specific instruments of today. Every strategy should be different, so we're going to pick on a common, modern architecture, list some of the typical threats, and lay out a plan of defense that adds some practical AI. Your situation is almost certainly different and nuanced, but hopefully this example's use of Judgment, Distance, Time, and Place is a good starting point to guide your solutions.

What You Expected to Happen

Our example is going to use a set of microservices, run in containers for better isolation, over HTTPS for encrypted communication, and a firewall configured properly to prevent anything but expected API use from passing through. A great start! The ops are solid. What could go wrong?

What Happens Instead

Probably before your first legitimate user logs in you'll start seeing your logs filling up with bots. You blocked regions that you don't expect users to be coming from with your firewall? That's nice, not every app has that luxury, but compromised systems and IoT devices cover every region. The more sophisticated ones are working together, have updated known exploit lists, and can alert people with destructive tendencies when they find an issue.

Your systems, designed to be helpful to developers and legitimate users, are equally helpful to attackers. Even wild, random attempts probably provide good intel on what kinds of services are running, what versions they're running, and more. This can escalate into increasingly targeted attacks.

Oh, and your end users are also on the receiving end of same style of attacks, so don't expect you can trust that all of their requests are actually from them.

But while there may be some basic algorithms and lookup tables for the bots, by and large they rely upon wide spread and fairly well known bugs. Enter AI. Deeply personalized - individualized even. Learning and working over long running workflows but at incredible speeds. Connecting the dots across multiple sources of information to look for unexpected correlations and make predictions. There's a reason the world is getting excited for Industry 4.0! Unfortunately, each of these represent a double edged sword.

What if you have an exploit that only exists for you, via the exponential combinations of some random sets of configurations, via the software or software integrations you use, or through APIs that are supposed to trust authorized users even if they're compromised? That's where AI and especially human assisted AI becomes weaponized, finding ever more creative ways in.

The Four Grounds of Defense, AI Edition

Before we begin formulating a defense, a word of warning as one last story from Gentleman Silver.

There was a cunning Doctor at his first going to sea, being doubtful that he should be sea sick, an old woman perceiving the same, said unto him: "Sir, I pray, be of good comfort, I will teach you a trick to avoid that doubt. Here is a fine pebble stone, if you please to accept it, take it with you, and when you are on ship board, put it in your mouth, and as long you shall keep the same in your mouth, upon my credit you shall never vomit." The Doctor believed her, and took it thankfully at her hands, and when he was at sea, he began to be sick, whereupon he presently put the stone in his mouth, & there kept it so long as he possibly could, but through his extreme sickness the stone with vomit was cast out of his mouth. Then presently he remembered how the woman had mocked him, and yet her words were true.
-George Silver

Beware of magical thinking and, to pardon the pun, Silver bullets. Security is incredibly hard because it is thinking about what isn't or shouldn't be there, not how it should be. Advanced AI systems are also hard, and any technology advanced enough lures humanity into the magical thinking fallacy.

That doesn't mean we should give up, but it does mean that you should invest in thoughtful security strategies in proportion to the risk of a breach.

OK, let's get to the diagram. It's getting a little crowded so, first let me show you just what's new:

Judgment & Measure

By pre-training a high speed model designed to recognize legitimate traffic from potential threats, you can keep an unblinking eye on service traffic at the load balancing layer, behind fully encrypted traffic but still blind to confidential field level encryption of things like personally identifiable information (PII). The job of the classifier is to measure the signature of communications and place a threat score on it, including dimensions of time and coordination of multiple requests.

It does not log, it only scores at a rapid pace and events that reach a high enough threat level are then passed on for further evaluation. Like a fencer circling and watching for signs of attack with the intuition of experience, the classifier is continuously taught by real events in a side process that doesn't bottleneck your high performance services.

Legitimate volume spiking and you need to start letting traffic through without it all being seen? Begin randomly picking messages instead so that you don't totally lower your defenses.

Time & Place

Once the ML model has found something of interest, that's when you power up a dedicated AI service to do the heavy lifting. Next generation AI security agents are designed to learn new attack vectors as they come in, deal with them, and update the more static services to watch out for them in the future. They also report back to your security team so that potential vulnerabilities can be patched. In the case of ongoing, active attacks, additional tools can be made available for real-time responses - AI empowered humans taking the wheel.

OK, you're under a new form of attack. Sure, you need to stop it, but you also need to learn from it. Isolate the attack, picking your own higher ground, so you can safely take your time to learn. For example, your defensive AI can trigger a "honeypot" environment that tricks the attacker into thinking they're talking to your real services but instead their every move is being studied against a false, mock server.

Here's what it looks like altogether, with a much more balanced approach to security.

As the tools continue to evolve, so will the strategies, but the fundamentals will remain the same. Embrace new tools without forgetting the timeless lessons of security, and risk can be managed in this new arms race. In doing so you not only protect your systems, but your customers and employees. There's much more to be said, but for now, let's all adapt and learn together to face fresh challenges.

Happy 2019!

Justin Williams — Mon, 07 Jan 2019 14:06:21 GMT

As the reality that a new year is already underway sinks in, we at Tinman Kinetics wanted to take a moment to look back at 2018 and this year ahead.

Last year was another record setter for data generation. According to Forbes, approximately 912.5 quintillion bytes were created in 2018 - roughly 1.2GB of data per human being on the planet. Meanwhile to crunch that data, even commodity hardware gained an average of 768 cores per processing unit at data centers big and small. The jump should be even bigger in 2019 - but of course data generation will continue to race to get ahead of our ability to compute it.

AI adoption spiked across the world in 2018 as well. According to McKinsey & Company, Robotic Process Automation kept the #1 spot with 23% internal capabilities in North America and 27% in Europe, and everyone else including China right there with North America at 23%.

General Machine Learning was right on its heels though, now at an average of 21% worldwide. These are internal capabilities, mind you, not just projects, which is impressive and goes to show why there's such a talent shortage in this rapidly growing field. Honorable mentions go to conversational language interfaces and machine vision, which both also broke 20%. Physical robots are still down around 16.5%.

At Tinman Kinetics, we had some looking back statistics of our own.

Our lead AI Scientist also gained a belt level in taekwondo, we launched our new website, 2.9 puzzles were constructed around the water cooler, and I personally grew, killed, and replanted a tree. The data says I should water it more often this time.

We're all incredibly excited about what's in store for 2019, and from our family to yours, we wish you all the best in this journey of life that we share.

Are you Ready for Automation?

Frank Trevino — Fri, 04 Jan 2019 21:29:53 GMT

Technology seems to grow exponentially these days with large companies such as Google and Amazon leading the charge with automation, but let’s not forget about the tech startups that are disrupting the automation market such as Uber, Airbnb and Slack, all valued at $1 billion or more and the many more startups looking to be the next unicorn. According to TechAsia, a new tech startup is created every three seconds around the world. All this technology drive is creating an age of automation not only on a personal usage level but also in the workplace. Investment in artificial intelligence alone is at 32% for software related services and growing.

As automation continues to move forward, it’s important to look back at the progression of emerging technologies that started this technology trend, starting with the early days of Business Intelligence (BI), Cloud, Big Data, IoT and now the emergence of Artificial Intelligence (AI). All of these technologies are driving the efforts for automation in the workplace, but most if not all companies large and small are challenged with:

• Where do I get started?
• What automation technology is right for our organization?
• What should we be measuring?
• How do we keep the momentum moving forward once we get started?

And there are also the organizational fears by not implementing automation:
• Losing a competitive advantage
• Lack of organizational efficiency
• Unable to recruit or maintain technology driven staff
• Becoming a dinosaur in the modern technology world

Understanding Automation
To begin, we must start with understanding automation. Automation is not just about technology, it is a strategy. Henry Ford integrated automation into his assembly line to increase time to market and operational efficiency. He didn’t utilize any new technology to drive his assembly line approach but put into place a well-thought out strategy. The difference today, technology is all around us and this is now part of the new equation in the digital transformation movement. Equivalent to digital transformation, automation is about people, process, product and technology working together in strategic harmony to create value.

Getting Started
First, automation within an organization must have a purpose. Like a marketing strategy, it must tie back into the sales strategy and business strategy to be successful, so must automation tie back into the corporate business strategy. So many organizations fall victim to a common trend in technology – Shiny Object Syndrome, or aka SOS. Business leaders will read an article or see a news clip introducing automation and how it is changing the way companies do business. This is when business leaders tend to act like children in a candy store. Their eyes open wide with excitement while making decisions based on untested theories regarding automation. This approach lacks an agenda, lacks the ability to scale and lacks an integrated approach. Again, there must be a purpose within automation as it ties back into the business strategy.

Second, automation must be validated. Validation consists of three key parts:
• Create a plan (People, Process, Product and Technology)
• Small Steps (Phased Approach)
• Stick to it (test, test, test)

A Plan to Validate
Creating a plan involves people, process, product and technology. The first thing to discuss with organizations who consider automation is understanding how this connects with your strategy – People, Process, Product and Technology

People – (Employees) understanding how your tech stack and people work together. Do they have the skillsets, are they open to transitioning, can they transition, do they have the right people to champion the technology? The worst situation is investing in technology with very little buy-in and after six months, the technology is no longer used. (Customers) understanding how automation can create value for your customers to keep them happy and coming back.

Process – Does the technology fit with the business processes already established? What if it changes the process? Is their alignment with other department processes? Understanding how to scale over time through existing and new processes.

Product - Will automation improve the product directly or indirectly? Will automation bring innovation to your product and give you a competitive advantage? Will automation lead to getting to market faster or increase quality?

Technology – how will it work with my existing technology? Is the technology flexible? Can the technology be adapted over time? Is the 3rd party technology company willing to make custom changes? What I mean by this is when an organization buys a technology stack but realizes only after that it doesn’t really give them the tools they need after a growth stage. This is something that is becoming more common in organizations.

Small Steps to Validate
The biggest challenge organizations battle with today is the investment. The investment comes in the form of people, time and money. It doesn’t make sense to jump into technology without understanding its value and also understanding the efforts to implement. The worst thing you can do is invest millions of dollars of time and money into automation without understanding the potential results. This approach goes back to the startup philosophy of creating a minimal viable product (MVP) that allows you to create a solution and test accordingly to make adjustments based on real-time feedback from users. Don’t build a full solution because you may fall into the trap that no one benefits from it, thus it brings no value.

Many companies struggle with how to integrate small steps, but this depends on your strategy and comfort zone. My goal is to make companies understand a phased approached to automation. This starts with task-oriented automation and eventually leads to functional-oriented automation. Task-oriented automation is used to help relieve a task or two of a persons’ busy schedule by automating menial tasks that take up too much time. An example of this includes using smart personal assistants, scheduling solutions, or an automated email system. This is perfect for companies who are new to automation and believe they lack the skills-set to integrate large solutions. As a progressive approach, functional-oriented automation is for organizations who are looking to more complex solutions such as Robotic Process Automation or RPA to help increase efficiencies across the company. These are larger companies who have the budgets and skillsets to implement such solutions. While the functional-oriented approach is more complex, it still requires small steps to validate.

Testing to Validate
Lastly, as you go through your small steps, every part of that process is testing. Generating data is the key to validate. Find data that predict results and remember, automation is only as good as the data we feed into them. Once it is determined what to test and how to test, remember to optimize your data points to gather details. While it is important to understand how to scale once automation is in place, it is more important to not scale through initial testing. Testing will tell you what is working and what is not, so adjustments can be made. This teaches us how to improve and properly implement while not losing sight of our goals and investment.

So, remember, test, test, test and when you fail, understand why, improve your efforts and test again.

In Conclusion
Automation brings many benefits from reduced production costs, enhanced quality & reliability and the ability to stay viable, all creating a competitive advantage. But is important to understand how automation brings value to your business through a strategic approach. Always consider your resources, understand your capabilities and determine the value gained from implementing automation. Your strategy starts with creating a plan with the right people on board who can lead the transformational process, understand the implications to the organization through analysis and who can implement potential game-changing technology.

Introducing Solution Spotlights

Justin Williams — Fri, 30 Nov 2018 14:38:26 GMT

Welcome to our Solution Spotlight corner. Here you will find some closer looks at real work and projects our experienced team has delivered in the past. We've got a lot to share but it takes a while to compile the most relevant elements together so please be patient.

In some situations we may want to aggregate and highlight an entire set related industry work we've done, and in others, we want to protect the privacy of customers and won't name names. Other times we'll put the spotlight on specific projects or customer interviews.

So watch this space, and stay tuned!

A Visual Assistant

Justin Williams — Fri, 30 Nov 2018 05:39:50 GMT

You may have noticed that our home page works a little different than most. It's sort of a "choose your own adventure" of point-and-click (or swipe-and-tap) so that, hopefully, visitors can find information relevant to what they are interested in more quickly. While also being presented with related paths they may find valuable but didn't know were options.

Like a conversation. But less talking out loud or typing.

AI Assistants through chat interfaces were the -Next Big Thing- around the 2016 time frame, but failed to engage audiences. The free form text took too long to get started, shallow knowledge bases meant that most free form text failed to bring up anything relevant (even if nuggets of good information was hidden away behind the scenes), and websites usually relegated the whole experience to a tiny "chat" window which was really only admitting it wasn't a core interaction.

Then voice AI Assistants were the -Next Big Thing- in 2018 and from Alexa to Google, AI Assistants began to finally live up to the hype. But companies like Amazon have gigabytes of data and thousands of engineers constantly working on making voice assistants more relevant. What if you were a company that didn't want to create your own Alexa but still have focused content about your knowledgebase, blogs, or other internal content?

“People worry that computers will get too smart and take over the world, but the real problem is that they're too stupid and they've already taken over the world.”
― Pedro Domingos

And for that matter, aren't most people pretty visual? Is there a better way, or at least a visual hybrid?

Our answer to that was released in 2018 and available as a packaged solution for companies of any size. Just like video games started with text adventures and moved on to visual point-and-click adventures, we think there's value in using a "semantic" path through even a small amount of content to help customers discover good info in an exploratory manner.

Using machine learning based style transfer, our AI effectively "re-paints" stock imagery and photography with relevant tagging with key content hand curated in order to add visual cues to content in an illusted manner - without paying thousands of dollars for thousands of custom art - all in the same style.

The AI then takes a content source - in our case, a small subset of blog posts - splits it up by category into bite sized pieces, auto-tags it based on semantic, conversational flow, and presents the results in a human editable database. Then, when visitors come to experience the interactions, the AI does live processing to weave unique narratives based on what it is detecting from the audience choices (or in advanced situations, previous knowledge or system integrations related to that specific individual).

Because the content is compiled down into a human-editable CMS, not only do you keep full control but it's also SEO friendly!

So, what do you think? We'd love to hear from you. Right now we don't have a lot of content but we'll add more over time. If you'd like to discuss the possibilities of integrating something similar into your organization or digital properites, please just let us know.

Creating a Celtic Knots to Study Language

Justin Williams — Fri, 05 Oct 2018 15:31:15 GMT

We've released a new study to investigate the link between personality and linguistic traits. Please check it out over at ByteOfScience.org! By participating you help the research around our AI XPRIZE project and get your own Celtic knot based on your unique personality.

IBM and others have already done a lot of interesting research around this topic, but most of that has been designed to predict personality based on a black box of language usage. These characteristics appear to be fairly accurate regardless of region, age, or other demographics and has been shown to work, when trained, across multiple languages.

We want to see if we can do the reverse - is it possible for an AI to take on the linguistic traits of someone based solely on their personality? Or, if not directly the linguistic traits, are there clear boundaries around the traits that are valid or invalid for a given personality?

To do this, we treat personality as the black box. This allows us to cast a much wider net when it comes to personality and include all kinds of theories and questions that need no validated research behind it. That's because we'll let machine learning explore the data as it is, and look for correlations that, perhaps, people wouldn't think of, in the same way the other studies don't know what the linguistic traits are that predict (more limited) personality traits.

Not all the data will lead to conclusive correlations, but given the success of the reverse, we are optimistic we'll find some new areas to take the research further. So go on, get your own, personal Celtic knot today and help contribute to this science!

Art with Heart 2018

Justin Williams — Thu, 31 May 2018 07:01:06 GMT

Could a custom Style Transfer convolutional neural network help feed people?

Thanks to Cafe 180 in Englewood, Colorado and a BETA photo re-painting charity event, it sure has. Thank you so much to all those who participated in this crazy experiment and to Cafe 180 for providing the food.

The Style Transfer technique has roots in Google's Deep Dream, which itself came out of research originally intended to understand how machine learning's black box worked for identifying visual objects. The first few layers of a digital neural network kind of make sense. Convolutional matrix transforms are done with paint programs like Photoshop to do simple things like emboss or otherwise highlight edges in an object. Deeper into the Convolutional Neural Networks, however, it got a little weird.
Image Source from Wikipedia By jessica mullen from austin, tx - Deep Dreamscope, CC BY 2.0

Tinman's focus is on empowering people through technology. By taking photos at or prior to the event, we helped even those of us who are artistically challenged into abstract painters. And, by partnering with an amazing charity like Cafe 180, we also supported a really important and impactful community program that provides nutritious choice in food with a pay what you can, when you can model.

A Digital Platform for Growth

Tinman AI — Thu, 02 Nov 2017 23:05:00 GMT

Software tailored to your particular needs is a great way to plan for growth. But growing can add unpredictability as well. Cognitive computing solutions can provide the flexibility you need to capture the full opportunity.

Here are just some of the raw tools that can help you craft new opportunities:

Mobile and web interfaces can be modular and content easy to update.
Content can be automatically evaluated for tone, brand, and intended audience.
Natural Language Processing (NLP) and Generation (NLG) can be used in everything from customer service tools and content narratives to employee coaching and visual digital assistants (like me!).
Automated security and quality agents can help you and your customers sleep well at night even during rapid change.
Machine Vision can classify products, supplies, and authorize personnel.
Robotic Process Automation (RPA) can help automate out repetitive but complex tasks and can even fill the gap for short-term integrations for aging software.
Automatic agents can oversee and analyze real-time and long running integrations.
Autonomous Data agents can mine Big Data for insights - or simulate scenarios when data is light.
AI trained on ethnographic research can predict customer reactions to new products, by region and demographic.
Self documenting microservices can make key data accessible from anywhere.
And of course many more in this rapidly evolving field.

That may sound like a lot, but we've got you covered! By building our platform from the ground up with cognitive computing, you can plan for adaptability.

New Tech, Old Fashioned Customer Service

Tinman AI — Thu, 02 Nov 2017 19:45:00 GMT

Artificial intelligence can be used to deeply customize every customer touch point, scaling personal service to everyone.

Funnel automated experiences into meaningful human interactions seamlessly, and let the AI keep your people engaged with customer history and emotional artificial intelligence at their finger tips.