Far More Than Bitcoin: 5 Ways Blockchain Turbo Charges your Brand

Far More Than Bitcoin: 5 Ways Blockchain Turbo Charges your Brand

Most people have heard of blockchain in conjunction with cryptocurrencies such as Bitcoin or smart contracts like Ethereum. While these applications demonstrate blockchain’s disruptive power, its decentralized, trustless technology has the power to do so much more for businesses and brands everywhere .

Greater Than the Sum of their Parts: The Convergence of AI and Blockchain

Greater Than the Sum of their Parts: The Convergence of AI and Blockchain

AI and blockchain are two of the most disruptive technologies in the world today. Whether it’s using machine learning to narrow down a customer’s preferences, or utilizing blockchain to create a secure, robust database, it’s hard to get very far in the modern marketplace without them.

Empathize, Iterate, Innovate: 5 Tips to Create Impactful and Inexpensive Prototypes

Empathize, Iterate, Innovate: 5 Tips to Create Impactful and Inexpensive Prototypes

Imagine you have an exciting new product. It’s something your team has spent months brainstorming, planning, tweaking, and honing until it matches your collective vision. You did everything right internally. But then, after spending all that valuable time, money, and resources, something doesn’t work as you thought when you release it to the world. Something you didn’t foresee stands between your product and a happy end user. Now you’re forced to start over from scratch.

Creating Symbiotic Intelligences: Why Design Thinking is Behind the most Successful AIs

Creating Symbiotic Intelligences: Why Design Thinking is Behind the most Successful AIs

AI is not a replacement for human thought. It’s a symbiotic partner. Successful applications of AI require more than just big data, powerful processing, and complicated algorithms. Designing truly useful AI requires a complete understanding of user needs, experiences, and, on an even deeper level, psychology.

Design Thinking for AI in Practice

Design Thinking for AI in Practice

Understanding the five stages of Design Thinking is the first step to putting this innovative methodology into practice. When put into practice, Liquid’s Design Thinking for AI optimizes business data and functions with a focus on understanding the human-centered experiences that both created the data and will be driven by the data DTAI develops intelligent solutions so you disrupt your industry before your competitors.

Planning your Machine Learning MVP

Planning your Machine Learning MVP

Testing is the most critical step of any successful machine learning project. It demonstrates whether your algorithms, weights, biases, and labels are correct or need to be improved. Read our white paper to learn the 10 critical steps to ensure successful testing of your machine learning application.

Only As Strong As Your Data: Using Feature Engineering to Build Robust AI

Only As Strong As Your Data: Using Feature Engineering to Build Robust AI

Garbage in, garbage out. I’m sure you’ve heard the phrase before. It can apply to relationships, dieting, working out, job performance, you name it: in order to get the best results, you have to fully commit to the best practices. Sure, it may sound simplistic, but it’s also true for machine learning projects. The quality of your model’s predictive output will only be as good as the quality and focus of the data it receives.

Overcome Your AI Barriers

You have likely felt the buzz in the business community about artificial intelligence (AI) – how it is transforming every business process from sales and marketing to customer service and throughout the entire supply chain. But despite all the talk, only one in five executives have deployed an AI solution to support core aspects of their business. The best place to start is find the right partner who has the experience, team and confidence to overcome the barriers.

Disrupt from Within: How Disruptive Innovation Can Help Large Enterprises

Disrupt from Within: How Disruptive Innovation Can Help Large Enterprises

Historically, disruptive innovators have started as outsiders. They’ve been the little guys, the low-level entrepreneurs, the plucky startups taking down market-leading incumbents.

But disruptive innovation doesn’t have to be this way.

How AI Improves Usability to Drive More Revenue

How AI Improves Usability to Drive More Revenue

Artificial Intelligence (AI) is one of today’s most exciting and versatile business tools. As Google’s CEO, Sundar Pichai says, “AI is more important than fire and electricity.” One of the most useful ways it can enhance our daily workflows is by removing the need to repeat processes or struggle with tedious endeavors when our time could be better spent on higher-value tasks. We are seeing more AI infiltration every single day.

They Call Me Mr. Upgrade

They Call Me Mr. Upgrade

Today, things tend to be a little different. Now we get major iOS revisions every year and with the introduction of Swift back in 2014, the annual upgrade has become complicated. To be clear, I’m actually okay with all of this happening, as it’s actually very good to see so much development effort being put into Swift, but as the person doing the upgrade, the details can be highly frustrating.

Design Thinking is Not Just for Techies

Design Thinking is Not Just for Techies

Design thinking on the business side is used as a guide to problem solving so that we can get out of our ruts and develop innovative and often out-of-the-box solutions. In a world where we have somehow managed to glamorize failure into a celebrated roadblock to success, Design Thinking allows you circumnavigate failure so that you can instead celebrate a prudent achievement.

Design Thinking—Beyond User Experience

Design Thinking—Beyond User Experience

Summarizing the key learnings from Northwestern’s Kellogg School of Management’s Design Thinking workshop and pulling together various resources as well as articles on the subject. After graduating with an MBA from Kellogg in 2005, I have been involved in many aspects of user experience and this workshop brought it all together for me.

Design Thinking consists of applying the (design) process of designing physical products to business decisions, services and even process improvement initiatives.

What I learned from using Amazon Alexa for a month

What I learned from using Amazon Alexa for a month

When Amazon Echo with Alexa service came out in November 2014 I was skeptical. A speaker with voice recognition seemed like an unnecessary oddity.

Alexa’s SDK has been open to third party developers for a year now. As a software engineer it is important to keep up with emerging technologies and learn about them. I purchased an Amazon Echo about a month ago and had an opportunity to interact with the technology and try out the SDK. Subsequently, I discovered these important truths:

Business Technology and Generations in Flux

Business Technology and Generations in Flux

Having grown up as Generation Y and watching technology grow at what seems like hyper speed, I can’t describe just how interesting it has been watching each generation interact with new technology, new devices and how much the latest generation (Millennials) has influenced the rapid request for change across many industries.

Natural Language Processing for the Layperson

Natural Language Processing for the Layperson

The usefulness of NLP is largely seen when combined with machine learning capabilities. With regards to being leveraged by businesses, when a machine can learn the semantics and context of the questions it is asked and statements it is given, it will enable businesses to unlock the potential of its large volumes of data to streamline processes and extract information without needing the help of a subject matter expert.

Machine Learning for the Layperson

Machine Learning for the Layperson

Machine Learning is creeping into companies of all sizes and I’ve found that many of those who want to implement it are those who aren’t in IT. Business clients are able to explain the results of machine learning within an application or set of applications, yet have trouble understanding exactly what machine learning actually is, how it works and why it takes longer than they think to get the results they want.

Working With Liquid Platform Kit— Demos (Part 1)

Working With Liquid Platform Kit— Demos (Part 1)

In previous tutorials, we went through CRUD with LPKTutorialOne, and Function IDs / QueryFilters / Composites with LPKTutorialTwo. In this tutorial, I want to go over common components that LPK offers, that will expedite the process of building your iOS application.

Note: The components covered in this tutorial offered by LPK are only supported for the iPad device.

Working with Liquid Platform Kit—Composites, Functions and Query Filters

Working with Liquid Platform Kit—Composites, Functions and Query Filters

In this tutorial, we will go through LPKTutorialTwo, where we go through a configuration driven method of displaying data on the app, and the basics of filtering.

Reminder of the LPK examples git hub rep, where you can get all applications / code.