AI

How to Prepare Your Business for AI

How to Prepare Your Business for AI

AI and machine learning are best-suited to specific types of tasks and these vary in complexity. For this reason, it is important to determine what you’re looking to accomplish so that you can intelligently configure and aggregate your data for the AI process to produce favorable results.

Creating Real Business Value with AI

Creating Real Business Value with AI

As more businesses are incorporating AI and ML into their strategy to reduce costs and create better products, they are gaining a competitive advantage over those holding on to traditional means of operation. Employed effectively, AI and ML will provide tide-turning returns for companies. If you’re looking to introduce AI into your business strategy, how do you choose the most effective business cases? How do you measure the empirical value?

Incorporating AI into Your Business

Incorporating AI into Your Business

As AI is increasingly adopted globally, it is vital to consider how AI can bolster your business. Gartner predicts that by 2020, 85% of customer interactions will be managed without a human. While AI is no silver bullet, when applied effectively, it can enable businesses to tune their customer interaction, marketing, and product design to competitive levels.

Consumers are the Most Disruptive Force

Consumers are the Most Disruptive Force

The most disruptive force in marketing today isn’t what you think. It’s not a machine. It’s not a device. It’s not an AI interface or a machine learning model or a conversational assistant. It’s the consumer. More specifically, it’s what consumers have come to expect from their brands. And if you can’t meet the needs and preferences of the next-generation consumer, your brand won’t stay relevant for long.

Untapped Potential: Optimizing Your Marketing with AI

Untapped Potential: Optimizing Your Marketing with AI

The surest way to grow your brand’s market share is to engage with consumers in a personal and meaningful way. By personalizing UX on every level, businesses give themselves the best chance at scaling their growth. But how do they do this in the realm of eCommerce, where there is often no human-to-human interaction?

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.

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.

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.

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.