AI, or Artificial Intelligence, is revolutionizing industries by enabling machines to simulate human intelligence and perform complex tasks. At Intel, we are at the forefront of this transformative technology, driving advancements in AI with our cutting-edge hardware and software solutions. Our powerful processors, accelerators, and optimized frameworks provide the computational horsepower required for AI workloads, delivering superior performance and efficiency.
With a focus on innovation, Intel is pushing the boundaries of AI capabilities, enabling breakthroughs in deep learning, machine vision, natural language processing, and more. Moreover, our comprehensive ecosystem of partners and developers paired with open platforms for experimentation and development empowers businesses to leverage AI effectively, making Intel the trusted leader in the AI sector. Together, we are unlocking the potential of AI to drive intelligent solutions and shape a smarter, more connected world.
From autonomous vehicles and surveillance systems to healthcare diagnostics and retail analytics, Computer Vision leverages the power of visual data to extract valuable insights and drive meaningful decision-making in various applications.
Computer vision is a field within AI that gives machines a human-like ability to see and understand the world. This cutting-edge technology is transforming lives by enabling a wide range of devices to extract meaningful data from digital images and video.
TD SYNNEX Vision AI Aggregated solutions bring computer vision and AI together to improve operational efficiencies, performance, and safety across various verticals.
The power of using Vision AI is to gain deeper insights into operational workflows while enhancing customer experiences, reducing operational costs, and utilizing sensor infrastructure to its maximum potential. Accelerate intelligent outcomes with AI that will decrease customers’ time to market, reduce downtime, and promote scale, all while increasing your revenue streams.
Generative AI is reshaping the boundaries of creativity and ability to generate new and original content, ranging from realistic images and music compositions to compelling stories and virtual environments.
Generative artificial intelligence describes the algorithms used to create new data that can resemble human-generated content, including audio, code, images, text, simulations and videos. This technology is trained with existing content and data, creating the potential for applications like natural language processing, computer vision, metaverse and speech synthesis.
Generative AI is not new. It’s the tech that created voice assistants, infinitely evolving games, and chatbots.
Recently, several powerful AI tools, such as ChatGPT and DALL·E 2, have been used as generative AI, enabling people to build apps on them, and to experiment and post the results online.
Intel’s Trusted Media team works to build generative AI applications with humans in mind. The team strives to create AI that improves people’s lives, limits harm and builds tools to make other technologies more natural. And it does it all with responsibility at each step of the process, not just the end.
In the past few years, generative AI has become more powerful – and therefore more capable of doing problematic things in a more convincing and realistic manner.
The Trusted Media research team is currently working on using generative AI to make 3D experiences more realistic. For example, Intel’s CARLA is an open source urban driving simulator developed to support the development, training and validation of autonomous driving systems. Using generative AI, the scenes surrounding the driver would look more realistic and natural. Intel’s generative AI approaches also simplify 3D creation and rendering workflows, saving hours for 3D artists and making games run much more quickly.
Machine learning is transforming the way businesses operate. From customized marketing and fraud detection to supply chain optimization and personalized medicine, machine learning turns complex data into real-world insights.
Machine learning is transforming the way businesses operate. From customized marketing and fraud detection to supply chain optimization and personalized medicine, machine learning turns complex data into real-world insights.
Machine learning is transforming the way businesses operate. From customized marketing and fraud detection to supply chain optimization and personalized medicine, machine learning turns complex data into real-world insights.
Myth
Intel Labs is developing algorithmic optimizations for large transformer models that will help sustain the growth of NLP.
Natural Language Processing (NLP) is a branch of artificial intelligence (AI) that focuses on enabling computers to understand, interpret, and generate human language. It involves the interaction between computers and natural language, allowing machines to process, analyze, and derive meaning from textual or spoken data.
NLP AI has numerous applications in various industries today.
Some common uses include:
Demand for Natural Language Processing (NLP) technology is rapidly ascending to a wide range of vertical markets, from healthcare to smartphones. With the NLP global market expected to grow to $341.7 billion by 2030, Intel Labs could not be more obsessed with making sure that practitioners have the resources to sustain this trajectory.
We are especially focused on developing advanced language technologies that will hasten NLP deployments. Along with our partners, we are working both internally and externally to develop and test these technologies and make sure they are optimized to run on Intel hardware. We are also working closely with open-source communities to accelerate the evolution of these solutions, as well as ensure that they are available to a wide range of users—not only the tech elite.
Our journey begins with addressing the most prominent challenges that data scientists and developers currently face when it comes to NLP deployments. These challenges include:
Dealing with very large, costly, and inefficient models
Wrangling large amounts of data to solve specific NLP tasks
The limited—albeit improving—limitations of machine understanding
Harnessing the potential of LLMs allows businesses to unlock the true power of language and revolutionize the way they interact with customers and process information.
LLMs, or Large Language Models, refer to advanced AI models designed to understand and generate human-like text based on the input provided to them. These models leverage deep learning techniques, particularly transformer architectures, to process and analyze vast amounts of textual data.
LLMs are trained on a wide range of topics and have the ability to generate coherent responses, provide information, and engage in conversations across various domains. They are capable of understanding context, generating contextually relevant responses, and offering insights based on the information they have been trained on.
LLMs have found applications in natural language understanding, language translation, content generation, and assisting with various tasks that require processing and generation of human language.
Myth