Progress announced the early-access release of Progress® MarkLogic® Server 12.
We have become accustomed to so many different technologies in our lives today. Most share a common history — there was a democratizing force that brought it from an abstract, unattainable thing we only heard about to something we can no longer live without. Take the computer — for decades, computers were larger than refrigerators and were only accessible to the largest companies or nations. Today though, most of the world carries one in their pocket. Mass-marketed desktop computers balanced cost and operational restraints with measured capabilities tailored to the needs of an individual; they were relatively easy to use, and one did not need to know how they worked to get value from them. They provided immense value for its users.
Looking at the world of emerging technologies, artificial intelligence (AI) appears to be the next technology on the cusp of breaking into the mainstream, thanks to the development and growing proliferation of no-code AI. A code-free technology that enables non-AI experts to implement and test their ideas without any need for a data scientist, no-code AI will prove to be a democratizing force within the AI industry enabling greater accessibility and use by businesses outside of the Fortune 100.
For businesses to remain competitive, they must invest time, money and resources into their AI capabilities. Luckily, with no-code AI, much like the desktop PC, there are varying levels of investment accessible to all instead of just those that can leap the historical barriers to entry. There is no need to establish a data-science practice, and there is no need to learn complex technologies.
To reap value, you need data and a system of automation; no-code AI brings the automation, and most organizations are already overflowing with data. A 2020 Salesforce report, which surveyed 100 global IT and engineering leaders, found that company departments utilizing workflow automation reduced time spent on manual processes by 66% and reduced cost by 46% compared to year-over-year outcomes. By streamlining manual processes through no-code AI models, businesses can scale faster while reducing the consumption of human time and increasing the accuracy of predictions.
Here are three key ways no-code AI is democratizing the technology:
1. No-Code AI Removes the Need for A High Degree of Training
It is no secret that a labor shortage exists for highly technical and skilled employees. Companies across all industries have difficulty finding and retaining qualified data scientists who can develop and create AI/ML models. This skills gap isn't going away anytime soon. No-code AI workflows empower citizen data scientists, including business analysts and other subject matter experts, to create, train and deploy powerful machine learning models. Another benefit of no-code AI is the relatively flat learning curve, allowing it to be quickly taught, replicated, and scaled across departments. This enables employers to combat the skills gap within their workforce by incorporating no-code tools training into employee development and onboarding.
2. Quicker Model Creation and Faster ROI
For companies lucky enough to have a data scientist on their staff, no-code AI enables them to work faster and more efficiently than before. No-code AI provides data scientists with automation and reusability that allows quick delivery of prototypes and iterative improvements using model explainability, revealing areas of model weakness. By employing no-code AI, data scientists can easily pinpoint problem areas within models, allowing managers to address any issues before they manifest into greater dilemmas quickly. Optimizing these processes frees up valuable bandwidth for data scientists to focus on more specialized research and projects within the company.
3. Better Explainability + Bias Detection Are Baked In
The Silicon Valley ethos of “move fast and break things” is gone. After years of eroding trust by big tech, consumers and businesses want to ensure the tech they invest in follows the “first do no harm” principle. Because no-code AI is created with the goal of enabling non-data scientists to harness the power of AI, it needs to be embedded with a higher level of explainability and bias detection to reduce the risk of human error.
No-code AI has proven to be a simple yet powerful solution aiming to bring AI to the masses. By democratizing AI with improved accessibility, businesses, regardless of size, will be able to compete more aggressively with AI in their toolbox.
Industry News
Red Hat announced the general availability of Red Hat Enterprise Linux (RHEL) AI across the hybrid cloud.
Jitterbit announced its unified AI-infused, low-code Harmony platform.
Akuity announced the launch of KubeVision, a feature within the Akuity Platform.
Couchbase announced Capella Free Tier, a free developer environment designed to empower developers to evaluate and explore products and test new features without time constraints.
Amazon Web Services, Inc. (AWS), an Amazon.com, Inc. company, announced the general availability of AWS Parallel Computing Service, a new managed service that helps customers easily set up and manage high performance computing (HPC) clusters so they can run scientific and engineering workloads at virtually any scale on AWS.
Dell Technologies and Red Hat are bringing Red Hat Enterprise Linux AI (RHEL AI), a foundation model platform built on an AI-optimized operating system that enables users to more seamlessly develop, test and deploy artificial intelligence (AI) and generative AI (gen AI) models, to Dell PowerEdge servers.
Couchbase announced that Couchbase Mobile is generally available with vector search, which makes it possible for customers to offer similarity and hybrid search in their applications on mobile and at the edge.
Seekr announced the launch of SeekrFlow as a complete end-to-end AI platform for training, validating, deploying, and scaling trusted enterprise AI applications through an intuitive and simple to use web user interface (UI).
Check Point® Software Technologies Ltd. unveiled its innovative Portal designed for both managed security service providers (MSSPs) and distributors.
Couchbase officially launched Capella™ Columnar on AWS, which helps organizations streamline the development of adaptive applications by enabling real-time data analysis alongside operational workloads within a single database platform.
Mend.io unveiled the Mend AppSec Platform, a solution designed to help businesses transform application security programs into proactive programs that reduce application risk.
Elastic announced that it is adding the GNU Affero General Public License v3 (AGPL) as an option for users to license the free part of the Elasticsearch and Kibana source code that is available under Server Side Public License 1.0 (SSPL 1.0) and Elastic License 2.0 (ELv2).
Progress announced the latest release of Progress® Semaphore™, its metadata management and semantic AI platform.
Elastic, the Search AI Company, announced the Elasticsearch Open Inference API now integrates with Anthropic, providing developers with seamless access to Anthropic’s Claude, including Claude 3.5 Sonnet, Claude 3 Haiku and Claude 3 Opus, directly from their Anthropic account.