Below you’ll see some of the tech trends showcased during NVIDIA GTC that we hear about from TechRepublic.
Advanced generation with advanced search
A technology that aims to reduce AI “hallucinations” or inaccuracies, advanced search generation allows the generative AI model to check its work against external resources, such as scientific papers or documents. RAG appeals to enterprise customers because it increases the reliability of the generated content.
“AI factories” to increase storage and computing needs
Many NVIDIA GTC organizations have described themselves as “AI factories” that provide enterprises with access to the storage and computing power they need to create artificial intelligence.
NexGen Cloud, which calls this service “GPUaaS,” is among the companies that will provide access to NVIDIA’s 10 trillion-parameter Blackwell GPU (Figure A) later this year.
Ten trillion parameter jobs require a lot of compute, and organizations are betting they can create a business model by providing just the right amount of compute power to customers.
During a preview briefing on March 15, Greg Findlen, senior vice president of product management for data management at Dell, shared that data storage must support high-performance structured data as well as unstructured data, such as documents, images and video.
Edge AI
Organizations that focus on edge AI also took their place at NVIDIA GTC 2024, with a wide variety: robotics, automotive, industrial, healthcare, mission-critical systems, and retail.
Many of these were powered by NVIDIA’s Jetson robotics platform. Jetson Orin’s NVIDIA Metropolis microservices allow developers to use API calls to create generative AI capabilities, making robots more reactive and flexible to their environment.
Private AI for enterprises
Organizations are working on creating private generative AI that can securely access their own data while providing the flexibility of a publicly available AI like ChatGPT.
During the show, NVIDIA mentioned Mistral AI several times, which provides a large open source language model that customers can host on their own servers.
Copilots can draw on company-owned data
NVIDIA GTC features a wide range of AI Copilots that can draw answers from specific, company-owned structured and unstructured data.
]]>
The phones will use the built-in Gemini Nano, Google’s most efficient model for large languages, and gain access to Gemini Pro and Imagen 2 technologies for text-to-image conversion via the cloud.
“We will reshape the technology landscape, we will open a new chapter without barriers to unleash your potential,” TM Roh, the president of Samsung’s mobile experience division, told a crowd in San Jose, California.
Live Translate
Live Translate is one of the first features announced that will translate phone calls in real time in 13 languages and 17 dialects.
New New New
Users will have the capability to utilize AI-driven summariza tion and classification functions within Samsung’s native applications like Notes, Voice Recorder, and the keyboard.
The Imagen model will empower users to execute intricate photo editing operations within the Gallery app, offering a tool that can enhance photo quality but also raises concerns about the potential for creating deceptive images.
Chat Assist
Chat Assist is the next feature that Samsung has introduced. Chat Asyst takes on the editorial role when writing messages – both in formal and informal environments.
Circle To Search
Additionally, the upcoming phones will feature Google’s “Circle To Search,” enabling individuals to encircle text snippets, segments of images, or videos to promptly retrieve search results related to the highlighted content.
Anticipated to hit the market by the end of January, these new phones promise enhanced functionalities and a seamless user experience.
For more details about the new features visit here.
]]>The news comes after Jenson Huang’s statement at the annual J.P. Morgan Healthcare Conference that “This year, every industry will become a technology industry.”
The talk, which took place in San Francisco, followed a J.P. Morgan conference presentation delivered by Kimberly Powell, NVIDIA’s vice president of healthcare. In her talk, Powell announced that Recursion is the first hosting partner to offer a foundation model through the NVIDIA BioNeMo cloud service, which goes into beta this month.
Drug Discovery with Generative AI and NVIDIA DGX SuperPOD
Kimberly Powell also shared that Amgen plans to advance drug discovery with generative AI and NVIDIA DGX SuperPOD – and that BioNeMo is being used by a growing number of technology companies, pharmaceutical companies, AI software providers and system integrators. These include Deloitte, Innophore, Insilico Medicine, OneAngstrom, Recursion and Terray Therapeutics.
From chip design to drug design
Healthcare customers and partners invest over a billion dollars in NVIDIA GPUs each year – directly and indirectly through cloud partners.
NVIDIA’s founder and CEO traced the company’s involvement in healthcare to two research projects that caught his attention some 15 years ago. One at Mass General used NVIDIA GPUs to reconstruct computed tomography images, and another at the University of Illinois at Urbana-Champaign applied GPU acceleration to molecular dynamics.
“It opened my mind that we could apply the same methodology that we use in computer-aided chip design to help the world of drug discovery go from computer-aided drug discovery to computer-aided drug design,” he said, realizing that, “if we scale this up by a billion times, we could simulate biology.”
Jensen Huang further explains that after 40 years of advances in computer-aided chip design, engineers can now create complex computer systems entirely through simulation. In the next decade, the same may be true for AI-mediated drug discovery and design.
Collaborating on the Future of Drug Discovery and Medical Instruments
NVIDIA is propelling the field forward by building state-of-the-art AI models and powerful computing platforms, and by collaborating with domain experts and investing in techbio companies.
“We are determined to work with you to advance this field,” Huang said, inviting healthcare innovators to reach out to NVIDIA. “We deeply believe that this is going to be the future of the way that drugs will be discovered and designed.”
The company’s pipelines for accelerated healthcare include algorithms for cryo-electron microscopy, X-ray crystallography, gene sequencing, amino acid structure prediction and virtual drug molecule screening. And as AI advances, these computing tools are becoming much easier to access, Huang said.
Because of artificial intelligence and the groundbreaking work that our industry has done, we have closed the technology divide in a dramatic way,” he said. “Everybody is a programmer, and the programming language of the future is called ‘human.’”
“A medical instrument is never going to be the same again. Ultrasound systems, CT scan systems, all kinds of instruments — they’re always going to be a device plus a whole bunch of AIs. The value that will create, the opportunities you create, are going to be incredible”, Huang said.
Beyond drug development, this transformation to a software-defined, AI-driven industry will also advance medical instruments.
]]>Humanoid robot company 1X Technologies, based in Mountain View, California, has raised $100 million in Series B funding with participation from Swedish venture capital firm EQT Ventures.
The company was able to raise more than $125 million in less than a year after raising $23.5 million in Series A2 funding from OpenAI and Tiger Global in early 2023.
This funding will support the production of safe and advanced androids at commercial scale. 1X Technologies’ biggest goal to date is to meet global employee needs.
The funds will also support 1X’s corporate customers in logistics and security.
NEO – the new home assistant
Meet NEO
The humanoid robot company has intentions to use the new capital, for its second generation Android NEO. Designed as a bipedal humanoid, NEO has a mission to help with everyday domestic activities.
The company asserts that what distinguishes NEO from other humanoid robots is its gentle and inherently secure design. In contrast to industrial machines, NEO is devoid of pinch-points or potential hazards, aligning with our dedication to providing a secure and user-friendly Android for consumers.
This focus on safety is crucial in bringing our vision to fruition, aiming to introduce a dependable and practical android into everyday life.
NEO’s soft construction resembling human features makes it safer and more comfortable than other robots. With a head, arms and legs similar to our own, NEO interacts with the world in a familiar way, performing activities such as walking, grasping objects and expressing emotions through facial cues.
Although NEO finds application in various sectors such as security, logistics, manufacturing, machine control and complex task management, its overall vision extends to becoming a valuable home assistant.
Envisioned for a long-term role in performing activities such as cleaning and organizing, NEO aims to integrate seamlessly into home life, increasing convenience and support for users.
While the company’s EVE android is currently working in logistics and guarding serving the enterprise market, NEO will be introduced into domestic environments, entering the household market first. It is on a fast track to market release and will be launched and available for consumers to pre-order within a short time.
]]>These enhancements, introduced at the CES technology event, allow GeForce RTX GPU owners to generate images in real time, thereby saving significant time in video production. The improvements to these models also aid in more efficient and streamlined workflows.
Each year, the CES event gathers the world’s most influential tech giants to showcase their most innovative and advanced technologies.
The improvements Ayesha Asif writes about allow GeForce RTX GPU owners to generate images in real time and save the time it takes them to generate videos. Improvements to the models also help improve and facilitate workflows.
Features of the Stable Diffusion models presented at CES
The new distillation technology built into the SDXL Turbo that allows image generation in just one step helps to achieve the most advanced results possible.
Up to four images per second
NVIDIA hardware accelerated by Tensor Cores and TensorRT can create up to four images per second while enabling access to SDXL’s real-time image generation for the first time ever.
Low-Rank Adaptation (LoRA) is a learning technology for fine-tuning stable diffusion models. Combined with the Latent Coherence Model (LCM), the LoRA checkpoint provides the ability to shorten the process past the sampling required to create a stable diffusion image.
LCM-LoRA runs up to 9 times faster as it uses only four steps (compared to the traditional 50 steps). In addition to this, it is important to note that the LCM-LoRA model is accelerated by TensorRT optimizations.
Stable Video Diffusion by Stability AI is their first foundation model for generative video based on the image model Stable Diffusion. Stable Video Diffusion runs up to 40% faster with TensorRT, potentially saving up to minutes per generation.
]]>Simultaneously, OpenAI has introduced the GPT Store, a one-stop marketplace for AI-driven applications and services. This store enables developers and businesses to showcase and monetize their AI-based solutions, creating an ecosystem of AI tools and applications accessible to a wider audience. The GPT Store is expected to catalyze innovation by encouraging the development of diverse applications, ranging from language processing tools to complex data analysis software.
Both ChatGPT Team and the GPT Store are built on OpenAI’s cutting-edge language models, ensuring high-quality, efficient, and versatile AI solutions. These initiatives mark a significant step in OpenAI’s mission to democratize access to powerful AI technology, potentially ushering in a new era of AI integration in everyday life and work.
]]>Governor Shapiro emphasized the significance of embracing technological advancements to stay ahead in the modern world.
“Generative AI is here and impacting our daily lives now — and we’re harnessing its benefits while mitigating its potential risks,” he stated.
This initiative marks a historic step in the practical application of AI technologies in government operations.
The collaboration with OpenAI, a leading AI research lab, signals Pennsylvania’s commitment to adopting cutting-edge technologies. By integrating ChatGPT Enterprise into the state’s workflow, Pennsylvania sets a precedent for other states to follow. This initiative is expected to bring about transformative changes in the way government services are delivered, promising increased efficiency and improved public service outcomes.
As the pilot progresses, the Commonwealth will be closely monitoring the impact and effectiveness of Generative AI in its operations, ensuring that the benefits are maximized while addressing any challenges that arise. This bold move by Pennsylvania could pave the way for widespread adoption of AI technologies in government operations nationwide.
]]>These ongoing transformations are reshaping the technological realm, exerting a profound influence on both consumer experiences and business practices.
Today, we’ve curated a selection of key technology terms and keywords for 2024, according to Techopedia, that offering valuable insights that can prove instrumental in staying abreast of the ever-changing tech landscape.
Artificial General Intelligence (AGI)
AGI is a form of artificial intelligence (AI) that mirrors human cognitive abilities, allowing it to perform various tasks and make complex decisions independently. This evolution in AI technology is not just about computational sophistication, but about creating systems that can independently reason, learn, and adapt across domains. Although AGI is still a distant dream, in 2024 the hype and expectations will continue to gain momentum.
For consumers: the advent of AGI promises to introduce more advanced and flexible AI assistants into everyday life, capable of understanding and performing tasks at a level previously only associated with human intelligence. This could revolutionize the way consumers interact with technology, offering personalized and intuitive assistance in everyday life – from home management to personalized education and health advice. AGI’s potential to improve the user experience is huge, providing more natural, efficient and effective interactions with technology.
For business: AGI provides huge opportunities for innovation and transformation across multiple sectors. AGI can lead to more accurate risk assessment and financial modeling in finance. In healthcare, it can enable more accurate diagnostics and personalized treatment plans.
Phygital Convergence
In 2024, phigital convergence will become a buzzword for transformation, representing the seamless integration of the physical and digital realms that will have a profound impact on both consumer experiences and business strategies.
For consumers: digital convergence offers an enriched experience where the boundaries between the online and offline worlds blur, providing unparalleled convenience and engagement. Consumers benefit from the flexibility and efficiency of digital solutions while retaining the tangible, sensory experiences of the physical world. For example, in retail, customers can explore products online and try them out in-store, or use AR to preview products in their own space before purchasing them.
For businesses: digital convergence is going from a trend to a strategic imperative. It is forcing businesses to rethink and redesign customer interaction models, ensuring a seamless and consistent experience across digital and physical channels. Retailers, for example, are rethinking store layouts to incorporate digital touchpoints, leveraging IoT for inventory management, and using AR for interactive product demonstrations.
Hyper-Personalization
In 2024, Hyper-Personalization is expected to be a key trend that will revolutionize consumer engagement and business strategies. Hyperpersonalisation uses artificial intelligence and machine learning (ML) to create customer experiences that are not just personalized, but deeply individualized. Through the use of extensive data analytics, including customer journey mapping and personalized content, Hyper-Personalization enables businesses to respond in real-time to changes in customer behavior, creating unique and relevant touchpoints that resonate on a personal level.
For consumers: embracing hyper-personalisation means moving to experiences that are intricately tailored to individual preferences and behaviors. Consumers can expect more intuitive and engaging interactions with brands, with services and content tailored to their needs and interests. This can take many forms, from online shopping experiences that offer products based on past behaviors and preferences, to content channels that adapt dynamically to reflect individual interests and interactions. The result is a more satisfying and engaging consumer experience that fosters a deeper connection with brands.
For businesses: hyper-personalisation offers the opportunity to significantly increase customer loyalty and lifetime value. This approach allows businesses to attract and retain customers by consistently delivering highly relevant and personalized experiences. However, achieving this level of personalization requires a sophisticated understanding of data analytics and customer privacy. Businesses must be able to collect and analyze large volumes of data while ensuring compliance with data privacy regulations and maintaining customer trust.
Sentiment Analysis
Sentiment analysis is set to maintain its buzzword status, influencing areas from online reputation management to the upcoming UK and US elections, driven by the ongoing impact of AI and machine learning on strategic approaches. Fueled by advancements in AI and machine learning, sentiment analysis deciphers intricate emotional cues in textual data, providing profound insights into public sentiment and consumer behavior.
For Consumers: Sentiment analysis significantly improves the consumer experience. Businesses can deliver more empathetic and efficient customer service by accurately assessing and responding to consumer emotions and feedback. This technology empowers companies to anticipate consumer needs, fostering personalized interactions and enhancing product offerings. Consumers enjoy a heightened sense of being heard and understood, cultivating stronger connections with brands and services.
For Businesses: Sentiment analysis offers crucial insights into customer perceptions and emerging market trends, enabling businesses to swiftly adapt their strategies. This leads to more targeted and successful marketing efforts, product improvements based on customer input, and enhanced risk management. Additionally, sentiment analysis plays a vital role in crisis management, allowing businesses to identify and address potential issues before they escalate.
Collaborative Ecosystems
The anticipation is that Collaborative Ecosystems will redefine the business landscape, ushering in a significant shift towards integrated, cooperative models of operation and innovation. This collaborative approach facilitates the pooling of diverse resources, skills, and insights, fostering a culture of innovation, reducing costs, and creating new forms of value.
For Consumers: The emergence of Collaborative Ecosystems brings a host of benefits for consumers. They can expect more holistic and integrated solutions that elevate the quality and diversity of products and services. This interconnected approach results in smoother, more cohesive experiences where technologies and services from various sectors seamlessly converge. This integration can lead to innovative solutions, higher-quality products, and more efficient services, ultimately enhancing overall consumer satisfaction and experience.
For Businesses: Engaging in collaborative ecosystems presents an avenue for innovation and market expansion. It offers enterprises the opportunity to break free from traditional silos, nurturing cross-industry partnerships that can result in the creation of new products and services. However, successful participation requires a commitment to effective collaboration, strategic integration, and often a willingness to share data and insights.
Sustainability/ESG
Beyond a mere tech buzzword, the focus on Sustainability and Environmental, Social, and Governance (ESG) considerations is set to gain momentum in the coming year, propelled by the Corporate Sustainability Reporting Directive (CSRD) in the European Union. This directive, mandating extensive climate impact reporting, is poised to profoundly influence global corporate practices and investment strategies.
For Consumers: Consumers are increasingly mindful of the environmental and social impact of their purchases, fostering a preference for sustainable brands. This inclination is expected to intensify, with consumers playing a central role in advocating for sustainability through their purchasing decisions.
For Businesses: Embedding ESG principles is evolving into a fundamental aspect of achieving long-term profitability and resilience. The CSRD compels companies to integrate sustainability into their operational and strategic decision-making processes. This entails a comprehensive reassessment and potential restructuring of supply chains, heightened investment in sustainable technologies, and a commitment to transparent and accountable reporting on sustainability metrics.
Augmented Reality (AR) & Extended Reality (XR)
Extended reality technologies are progressing beyond novelty, evolving into indispensable tools across various sectors, thanks to their immersive and interactive capabilities.
For Consumers: AR and XR are reshaping consumer engagement by providing enhanced, interactive experiences that seamlessly blend the digital and physical realms. In retail, for instance, AR allows customers to virtually try on clothing or preview furniture in their homes before making a purchase, significantly enhancing the decision-making process.
For Businesses: The impact of AR and XR on businesses is significant. In sectors such as construction and manufacturing, AR assists in visualizing projects in 3D, enhancing accuracy and efficiency throughout the design-to-execution process. This visualization capability proves invaluable for architects, engineers, and designers, streamlining the transition from conceptualization to realization.
Quantum Computing
While it has long been a buzzword, quantum computing is anticipated to move beyond theoretical research in 2024, transitioning into a practical and impactful technology that holds substantial benefits for both consumers and businesses.
For Consumers: The arrival of quantum computing is poised to profoundly revolutionize everyday life. Its unparalleled computational power has the potential to drive significant advancements in fields directly impacting consumers, such as medicine, environmental science, and logistics.
For Businesses: Quantum computing opens up a frontier of untapped potential for the business sector. In finance, it could revolutionize risk assessment and fraud detection, providing insights currently unattainable with classical computing methods. In the pharmaceutical industry, it has the potential to significantly reduce the time and cost associated with drug development, enabling quicker responses to global health challenges.
]]>“Climate change is a real and pressing issue that we must find new ways to address as quickly and efficiently as possible, including through today’s most advanced AI technologies,” said Alessandro Curioni, IBM Fellow and Vice President, Accelerated Discovery at IBM.
IBM continues to develop its strategy for artificial intelligence models that are trained on geospatial information such as satellite imagery and provide the capability to address climate change.
Alessandro Curioni, IBM Fellow and Vice President, Accelerated Discovery at IBM added “AI foundation models utilizing geospatial data can be a game-changer because they allow us to better understand, prepare and address the many climate-related events effecting the health of our planet in a manner and speed never before seen. We are hopeful these technologies can help accelerate the rate at which we derive and apply solutions for a safer and healthier planet for future generations”.
Unlike traditional AI models tailored to specialist tasks, knowledge-based geospatial models – spanning satellite and weather data – create knowledge representations from petabytes and exabytes of climate-related data that can facilitate accelerated and streamlined discovery of environmental insights and solutions.
” This research underscores the vital role of AI in tackling global issues, emphasizing the urgency of continued exploration and innovation. By harnessing the power of AI, we are not merely addressing challenges; we are proactively shaping solutions for a sustainable future. In a world confronted by unprecedented challenges, MBZUAI stands at the forefront of pioneering research in AI, recognizing the transformative power it holds”, said professor Tim Baldwin, MBZUAI Acting Provost.
These models can also be refined and applied across multiple domains defining or revealing climate change, from flood detection to fire scarring.
Beyond their initial commitment to build and deploy a geospatial foundation model, IBM and NASA have also announced work on a new, separate AI foundation model for weather and climate. By applying AI technology from IBM, the model aims to improve the accuracy, speed and affordability of weather forecasting and other climate applications.
Sample applications of the model not only include forecasting, but also super-resolution downscaling, identifying conditions conducive to wildfires, and predicting meteorological phenomena. IBM researchers will work alongside NASA domain experts to train and validate the model.
]]>DeepMind claims to have made a new discovery that could lead to the creation of new materials for future technologies, Silicon Republic reports.
The company said that one of its artificial intelligence models has discovered 2.2 million new crystals, 380,000 of which could be used to create new materials that could drive various forms of technology.
“Our research boosted the discovery rate of materials stability prediction from around 50pc to 80pc – based on an external benchmark set by previous state-of-the-art models,” DeepMind said in a blog post.
According to DeepMind, these materials could be used to develop devices such as superconductors, supercomputers and next-generation batteries for electric vehicles. The company said it has provided researchers with the predictions of stable materials made by the artificial intelligence model.
“We also managed to scale up the efficiency of our model by improving the discovery rate from [less than] 10pc to [more than] 80pc – such efficiency increases could have significant impact on how much compute is required per discovery”, the company continued in the blog post.
The AI model, known as Graph Networks for Materials Exploration (Gnome), is denoted as a “graph neural network model.” It employs two distinct pipelines for the exploration of stable, low-energy materials.
According to DeepMind, one of these pipelines generates potential material candidates with structures resembling known crystals. The second pipeline takes a more experimental approach, employing a “randomized approach” based on chemical formulas.
The company states that the outputs from both pipelines undergo evaluation through “established density functional theory calculations” before being incorporated into the Gnome database.
DeepMind asserts that external researchers have successfully synthesized 736 novel materials in laboratories, leveraging predictions from the AI model. However, the company emphasizes that the realization of new technologies stemming from these materials hinges on our capability to effectively manufacture them.
“Our research – and that of collaborators at the Berkeley Lab, Google Research and teams around the world – shows the potential to use AI to guide materials discovery, experimentation and synthesis,” DeepMind said.
In the preceding year, DeepMind declared a significant scientific advancement as its AlphaFold model successfully predicted the structure of nearly every known protein in the scientific domain, totaling more than 200 million.
]]>