Revolutionising Communication: The Game-Changing Potential of Language AI. Are you ready?
The launch of GPT-4 heralds a new era in the rapidly evolving landscape of natural language processing, unlocking many lucrative business prospects and fueling the growing appetite for cutting-edge AI solutions.
This technology has the potential to revolutionise the way we operate by improving communication, increasing efficiency, and enabling us to analyse vast amounts of data like never before. Some possibilities include enhancing customer service, automating repetitive tasks, personalising marketing efforts, and unlocking valuable insights from unstructured data.
Dive into this week’s captivating collection of the finest artificial intelligence articles. Embark on an exhilarating adventure into the fascinating realm of AI!
AI’s Regulatory Framework Begins To Take Shape-And None Too Soon
The private sector must be a serious partner in regulating AI use and risks.
The newly released Artificial Intelligence Commission Report (“Report”) from the U.S. Chamber of Commerce provides one of the first substantive templates for a regulatory framework of artificial intelligence. It’s an important step, given that the speed of AI roll-out is far outpacing the preparation of a legal framework to regulate its investment, oversight, and implementation.
Thus the Report may prove an important resource for corporate leaders who intend to invest in AI technology, desire guidance on the use of AI by their companies, or seek to influence the development of AI technology.
8 green computing best practices
Public, private, hybrid or consortium, each blockchain network has distinct pluses and minuses that largely drive its ideal uses — and will determine which one is best for you.
According to Gartner, enterprise production use cases are expected to grow by double-digit percentages in 2021. However, different use cases require different types of blockchain.
There are four main types of blockchain networks: public blockchains, private blockchains, consortium blockchains and hybrid blockchains. Each one of these platforms has its benefits, drawbacks and ideal uses.
CIOs Start To Rethink Artificial Intelligence
Is it possible that artificial intelligence is not all that smart?
Just about every CIO has heard about artificial intelligence (AI) and the wonderful things that it can do. In fact, by now we are all using some form of AI in our mobile phones and in those Alexa speakers that everyone has laying around their homes. What these devices have been able to accomplish using AI technology have been very impressive; however, the future has always been brighter.
We’ve been told for a long time that this is just the start of the AI revolution and that we should expect great things to be coming our way in the future. However, should CIOs really believe this? Is the promise of AI all that it’s been made out to be?
The Problem With AI
CIOs need to understand that a funny thing happens among engineers and researchers who build artificial intelligence once they attain a deep level of expertise in their field. It turns out that those that understand what actual, biological intelligences are capable of, conclude that there’s nothing “intelligent” about AI at all. In a certain sense artificial intelligence is a bad name for what it is companies are doing here.
After year of downsizing, DataRobot unveils new AI platform
Built for data scientists by data scientists
But today, the company capped a comeback by unveiling its new AI platform 9.0, along with deeper partner integrations, AI accelerators, and redesigned service offerings — which are all focused on helping organizations “derive measurable value from their AI investments.”
The new AI platform includes Workbench, a user experience that supports users with code-first and no-code approaches; reduced enterprise risk through bias mitigation, centralized model monitoring and automated model compliance; and new AI service packages.
Augmented intelligence for everyone everywhere
The explosion in data will drive the need for representations such as knowledge graphs that reveal patterns, relationships and connections among concepts and facts.
Everywhere you look, organizations are facing resource limits. If necessity is indeed the mother of invention, these resource constraints will give birth to new and disruptive innovations in 2023.
Every new wave of technology over the past 20 years has responded to the growth in data generated by people and things connected to a worldwide network. Organizations routinely use data from sources as diverse as client transactions, internal systems, external partners, the Web, social media and the physical world to inform their strategies, plans and operations. Just as every enterprise comes to embrace a data-driven approach to business, every employee in an enterprise will want to take greater advantage of all the data they can access.
To enable everyone to extract value from data, developers will need to build new interfaces to new systems that process and store data while working harder to preserve data privacy.
GPT stands for Generative Pre-trained Transformer. It is a neural network machine learning model which is trained using data on the internet to generate any type of text. This sophisticated neural network is used to train large language models (LLMs) to simulate human communication.
The model tracks words in a sequence, allowing it to learn both the context and meaning of the language. The GPT model focuses on text-only, allowing it to use artificial intelligence to analyze what the user is asking and effectively generate text.
It has taken the artificial intelligence world by storm with its conversational abilities, contextual information, and more. The model can handle tasks such as text summarization, code generation, and provide valuable insight within seconds.
THE DIGITAL EYE
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