3 Top Artificial Intelligence Stocks to Buy Right Now

3 Top Artificial Intelligence Stocks to Buy Right Now

Every so often, a new technology comes along that fundamentally changes the world. Consider the discovery of electricity, the invention of the automobile, and the creation of the internet — all three sparked dramatic transformations, boosting productivity and efficiency across industries.

The developments surrounding artificial intelligence (AI) are likely to have a similar impact. And enterprises that use AI effectively could gain a meaningful advantage over their peers. In fact, companies like Coupa Software (NASDAQ:COUP), CrowdStrike Holdings (NASDAQ:CRWD), and Palantir Technologies (NYSE:PLTR) appear to be doing just that.

Here’s what investors should know about these three top AI stocks and why they are a buy right now.

Computer chip labeled Artificial Inteligence Chipset

Image source: Getty Images.

1. Coupa: Business spend management

Coupa’s business spend management (BSM) platform connects more than 7 million suppliers with over 2,000 buyers. This helps suppliers reach a wide audience of potential customers, and it provides buyers with an extensive catalog of products. Moreover, Coupa’s platform helps clients realize cost savings and work more efficiently, an advantage made possible by artificial intelligence.

Coupa Community Intelligence is the company’s AI-powered recommendation engine. By applying AI to transactions occurring on its platform, Coupa is able to make prescriptive suggestions that help its clients spend money more efficiently and reduce supply-chain risk.

The Coupa Community Intelligence solution is a key differentiator that separates the company from its competitors. In fact, during the latest earnings call, CEO Rob Bernshteyn said: “No other company in our industry can provide … a platform with real-time prescriptions.” That’s a big advantage, and it has helped make Coupa the market leader in procure-to-pay suites.

Currently, management estimates the company’s market opportunity at $56 billion, but that figure should continue to expand as more enterprises implement digital solutions to drive efficiency. And as that trend plays out, Coupa’s best-in-class BSM platform should help it capture value and reward long-term shareholders.

2. CrowdStrike Holdings: Cloud security

CrowdStrike was founded in 2011, five years after Amazon Web Services (AWS) went live, sparking widespread adoption of cloud computing. Recognizing the benefits, CrowdStrike pioneered cloud security, designing the first cloud-native, AI-powered cybersecurity platform: CrowdStrike Falcon.

Unlike legacy solutions, the Falcon platform is capable of collecting and analyzing data on a massive scale. In fact, CrowdStrike’s Threat Graph processes more than 5 trillion data points each week, and that number will continue to climb as new clients join.

That’s important — as the platform collects more data, the AI-powered Threat Graph becomes more intelligent, improving its ability to detect malicious activity. Moreover, once a threat is identified in one client’s environment, it can be blocked for all clients immediately. This creates a network effect that enhances CrowdStrike’s preventative capabilities over time.

As a result, the company has won a reputation for industry-leading threat detection. In fact, SolarWinds became a CrowdStrike customer after the highly publicized breach of its Orion platform — an event that impacted up to 18,000 enterprises and cost an estimated $90 million, according to BitSight.

Additionally, in a recent benchmark test conducted by SE Labs, CrowdStrike’s Falcon platform achieved a perfect score in both detection and prevention use cases, while also registering zero false positives. In other words, Falcon is highly effective and very precise in its ability to defend endpoints and workloads. That should make CrowdStrike a long-term winner in the cybersecurity market.

3. Palantir Technologies: Big-data analytics

Machine learning is a type of artificial intelligence in which large amounts of data are used to train mathematical algorithms. Once trained, those algorithms are referred to as AI models. Ultimately, the goal is to build a model capable of accurate decision-making — but that only works if there are enough high-quality data to train the algorithms. That’s where Palantir can help.

Palantir’s two platforms — Foundry and Gotham — are built to support AI. Both of these software-as-a-service (SaaS) products allow clients to integrate enormous datasets, creating the input needed to train AI algorithms. These solutions also incorporate algorithm deployment infrastructure and feedback loops, which serve to improve the accuracy of the AI models over time.

Simply put, Palantir allows its clients to draw insights from massive amounts of data, empowering them to build more intelligent AI models. That’s why the U.S. Army Research Laboratory selected Palantir to help enhance its AI capabilities. Similarly, in the commercial sector, IBM has partnered with Palantir to build a low-code platform that simplifies the development of AI-powered applications.

Management estimates the company’s market opportunity at $119 billion, more than 100 times its trailing-12-month revenue. That gives this tech company plenty of room to grow in the future.

This article represents the opinion of the writer, who may disagree with the “official” recommendation position of a Motley Fool premium advisory service. We’re motley! Questioning an investing thesis — even one of our own — helps us all think critically about investing and make decisions that help us become smarter, happier, and richer.

Published at Fri, 09 Apr 2021 12:22:30 +0000

Listen up – Machine learning is revolutionizing hearing loss

ML is being leveraged with deep learning and advanced signal processing techniques at a level of detail previously impossible

9 April 2021

Haris Elias

There’s no shortage in the number of companies providing AI-powered hearing aids. Source: Pixabay.

  • Most hearing aid tech on the market has not changed for decades, but now machine learning is being leveraged at a level of detail previously not thought possible

As machine learning (ML) integrates itself into almost every industry – from automotive and healthcare to banking and manufacturing- the most exciting advancements look as if they are still yet to come. Machine learning as a subset of artificial intelligence (AI) have been among the most significant technological developments in recent history, with few fields possessing the same amount of potential to disrupt a wide range of industries.

And while many applications of ML technology go unseen, there are countless ways companies are harnessing its power in new and intriguing applications. That said, ML’s revolutionary impact is most poised perhaps when put to use for age-old problems.

AI-powered hearing aids

Hearing loss is not a new condition by any means, and people have suffered from it for centuries. The first electric hearing aid was designed in 1898 by Miller Reese Hutchison, with the first commercially manufactured hearing aids introduced in 1913. With an estimated 48 million Americans experiencing some sort of hearing loss, hearing aids can be a lifeline for many who struggle with the quality of their hearing.

And while it may seem hard to believe, today’s most predominant hearing aids on the market can be painful to wear having been designed 50-100 years ago. In response to a stagnant area of development, ML is being leveraged with deep learning and advanced signal processing techniques at a level of detail previously impossible.

Through the application of software-based solutions, ML algorithms can power hearing aids to detect, predict, and suppress unwanted background noise. Neural network models take structured and unstructured data and augment it with other data sets relating to the spectrum of age, language, and voice types. The data is then refined by being fed into neural network training, which begins a process of ongoing product improvement.

In an interview with Forbes, Andre Esteva, Head of Medical AI at Salesforce says that the limits of traditional approaches have been emphasized by the manual processes involved in acquiring data to mold it into a usable format, before preparing basic algorithms to be deployed to devices. ML training protocols, on the other hand, Esteva says, automatically processes data before updating themselves to redeploy.

“The effect is a significant reduction in product feedback cycles and an increase in the range of capabilities available. The beauty of this approach is that the underlying intelligence improves over time as the neural nets go through iterative training,” added Esteva.

Promising buzz

As of today, there are several companies providing AI-powered hearing aids. The most recent being Whisper, a startup that has recently obtained funds of around US$50 million as they prepare to go to production on their first product. The AI-powered hearing aids from Whisper self-tune over time, and continually improve with AI for better performance.

Elsewhere, MicroTech claims its Essentia Edge product scans environments to make changes to boost speech intelligibility, while Widex’s Evoke hearing aids combine real-time input with previously learned sounds from users and millions of other listening domains. The goal of introducing machine learning technologies in healthcare is to enhance the experience of patients and users. As intelligent innovative solutions continue to emerge in a field full of noise, the buzz around revolutionary tech seems to only get louder.

Haris Elias

9 April 2021

8 April 2021

8 April 2021

Published at Fri, 09 Apr 2021 11:48:45 +0000