LOS ANGELES, CA, Jan 29, 2024 – Concrete.ai, the company using GenAI to optimize concrete mix designs for efficiency, carbon, and cost savings, today announced the commercial availability of its field-tested, patented AI platform, Concrete Copilot. From the millions of possible mix designs, the platform generates those that are the most optimized for any combination of cost, performance, and carbon reduction, empowering producers to select the best mix for their use case.

Mix optimization is crucial to any concrete producer’s success, but the design process has become increasingly difficult with today’s complexity of supply chains, constant changes in material types and costs, and the vast array of complex performance data. And with a growing number of policies mandating low-embodied carbon material for construction projects, there is additional urgency for builders to reduce their carbon footprint, specifically within concrete production – which is responsible for 9% of worldwide emissions.

Producers are often left struggling to not only identify the right concrete mixes that meet requirements but also to introduce them into production quickly without disrupting plant operations or affecting performance and cost.

During Concrete Copilot’s extensive field testing with producers across the US, the platform optimized mix designs used in over 2,000,000 cubic yards of concrete – enough concrete to fill 681 Olympic-size swimming pools. The average material savings were $5.04/cubic yard, and the average carbon reduction was 30%. For most producers, these results were seen within just one month of activating the platform.

“I’ve spent 26 years working in the construction and ready mix industries and personally know the challenges concrete producers have to overcome to find the most economically viable mix designs,” said Alex Hall, CEO of Concrete.ai. “We built Concrete Copilot, so producers don’t have to choose between cutting cost and carbon. Our ultimate goal is to reduce the annual global carbon footprint of concrete by ~500 million tons just by optimizing concrete mixes with materials already in supply chains.”

Here’s how it works: Concrete Copilot first integrates with a producer’s current and historical data. Producers can select their optimization criteria based on their specific objectives. The platform then creates millions of mix designs in seconds and presents the optimal one to the user to approve or modify based on their judgment and experience, streamlining the design process from months to minutes.

Concrete Copilot uses the materials in a producer’s current supply chain, and when there are shifts in a material’s availability or cost, producers can rapidly create new mix designs. The platform also allows for quick evaluation of the many new sustainable materials entering the market each year, helping them to enter production quickly for an immediate environmental impact.

“Integrating Concrete Copilot into our existing software was a remarkably quick and smooth process. Using our own data and local materials, the tool efficiently streamlined our mix design process, allowing us to maximize materials cost savings and deploy the optimized mix designs into production faster,” said Chris Rapp, vice president and general manager of VCNA Prairie Materials. “This resulted in significant reductions in cost and carbon footprint.”

About Concrete.ai

Founded in 2021, Concrete.ai delivers cost-saving and embodied carbon reductions in concrete production through AI-assisted concrete design. The generative AI behind Concrete Copilot has been in development at UCLA’s Institute for carbon management for nearly a decade. Concrete.ai’s patented platform, Concrete Copilot, creates millions of possible mix designs that empower producers to identify the most optimal concrete recipe for any application.

To learn more, visit concrete.ai.

TEL AVIV, Israel, Jan 22, 2024 – Deci, the deep learning company harnessing artificial intelligence (AI) to build AI, announced today it is collaborating with Qualcomm Technologies, Inc. to introduce advanced Generative Artificial Intelligence (AI) models tailored for the Qualcomm Cloud AI 100, Qualcomm Technologies’ performance and cost-optimized AI inference solution designed for Generative AI and large language models (LLMs). This working relationship between the two companies is designed to make AI accessible for a wider range of AI-powered applications, resulting in the democratization of Generative AI’s transformative power for developers everywhere.

“Together with Qualcomm Technologies we are pushing the boundaries of what’s possible in AI efficiency and performance,” said Yonatan Geifman, CEO and co-founder of Deci. “Our joint efforts streamline the deployment of advanced AI models on Qualcomm Technologies’ hardware, making AI more accessible and cost-effective, and economically viable for a wider range of applications. Our work together is a testament to our vision of making the transformational power of generative AI available to all.”

Through the relationship, Deci will work with Qualcomm Technologies to launch two groundbreaking models. The first model is DeciCoder-6B, a 6 billion parameter model for code generation engineered with a focus on performance at scale. Supporting eight programming languages (C, C#, C++, GO, RAST, Python, Java, JavaScript), it outperforms established models such as CodeGen2.5-7B, StarCoder-7B, and CodeLlama-7B. In fact, in Python, DeciCoder achieves a 3-point lead over models more than twice its size, such as StarCoderBase 15.5B. The model also stands out for its remarkable memory and computational efficiency, boasting 19x higher throughput compared to similar models when running on Qualcomm’s Cloud AI 100.

The second model, DeciDiffusion 2.0, is a 732 million parameter text-to-image diffusion model that sets new standards by outperforming Stable Diffusion v1.5, operating at 2.6 times the speed with on-par image quality. Both models are meticulously optimized to leverage the full potential of the Qualcomm Cloud AI 100 solution. These models are designed to enable users across various industries to experience exceptional performance from the outset at a more competitive price point.

Both DeciCoder-6B and DeciDiffusion 2.0 were developed using Deci’s Neural Architecture Search Technology, AutoNAC, its proprietary, hardware-aware technology that democratizes the use of Neural Architecture Search for enterprises of all sizes. The distinctive architecture of both models ensures efficient scaling of batching while maintaining minimal memory usage and avoiding any increase in latency. Additionally, the models were designed to handle large batches, enabling maximal utilization of the computational power of the Qualcomm’s Cloud AI 100 cores. DeciCoder-6B and DeciDiffusion have been released under Apache-2.0 and CreativeML Open RAIL++-M Licenses, respectively.

About Deci

Deci enables deep learning to live up to its true potential by using AI to build better AI. With the company’s deep learning development platform, AI developers can build, optimize, and deploy faster and more accurate models for any environment including cloud, edge, and mobile, allowing them to revolutionize industries with innovative products. The platform is powered by Deci’s proprietary automated Neural Architecture Construction technology (AutoNAC), which generates state-of-the-art, efficient deep learning models’ architecture and allows teams to accelerate inference performance, shorten development cycles and reduce computing costs. Founded in 2019, Deci’s team of deep learning engineers and scientists are dedicated to eliminating production-related bottlenecks across the AI lifecycle.

For more information, visit www.deci.ai.

TEANECK, NJ, Jan 17, 2024 – Cognizant announced its collaboration with Microsoft on the launch of the Innovation Assistant, a generative AI-powered tool built on Microsoft Azure OpenAI Service, which will augment Cognizant’s internal innovation program, Bluebolt.

The Innovation Assistant is a pioneering tool designed to assimilate enterprise knowledge and enable greater creativity and innovation among teams of Cognizant employees working to solve client challenges across industries. The launch exemplifies Cognizant’s commitment to transforming human-machine collaboration through AI and advancing knowledge and innovation by leveraging the company’s vast technical and industry knowledge.

“The creativity and ingenuity of Cognizant’s people is one of the things that sets us apart in our industry, and we see our Innovation Assistant as a game-changer in the way we generate and implement ideas,” said Ravi Kumar S, Cognizant’s CEO. “Together with Microsoft, we are harnessing the power of generative AI to revolutionize our approach to innovation, with the goal of ensuring we, and our clients, stay ahead in a rapidly evolving business environment.”

The Innovation Assistant is integral to Cognizant’s Bluebolt grassroots innovation movement, which provides a framework for Cognizant employees anywhere and at any level, to contribute to the innovation process from ideation to implementation. Harnessing the power of generative AI for Bluebolt will help Cognizant employees develop a unique combination of virtual guidance and real-world support that can utilize the company’s full depth of expertise and co-innovation for the benefit of clients.

“It’s amazing to see the power of gen AI enable innovation at different levels of an organization with Cognizant’s Innovation Assistant. They have used AI to create a platform that unlocks the potential of individuals and teams,” said Puneet Chandok, president, Microsoft, India & South Asia. “Built on Microsoft Azure OpenAI Service, Cognizant’s platform is a force multiplier that aims to enable customers to gain access to insights from enterprise data and stay ahead in the ever-evolving digital landscape.”

Cognizant is dedicated to maintaining the highest standards for responsible and ethical AI, focusing on safety, security, privacy, transparency and inclusion. The Innovation Assistant is designed to generate context-based ideas and solutions while safeguarding sensitive information and client confidentiality.

For more information on Cognizant’s approach to generative AI and the company’s commitment to responsible AI, visit here.

About Cognizant

Cognizant engineers modern businesses. They help their clients modernize technology, reimagine processes and transform experiences so they can stay ahead in our fast-changing world.

For more information, visit www.cognizant.com.

BERLIN, Germany and LOS ANGELES, CA, Jan 12, 2024 – 1000 Kelvin has announced the full commercial availability of its AI-driven software, AMAIZE, at Formnext 2023. The company is also unveiling its first integrations with commercial 3D printer manufacturers—including EOS—and customers, including a California-based rocket launch provider.

1000 Kelvin’s software acts as an autocorrect copilot for 3D printing. By using a physics-informed AI, AMAIZE automatically identifies and corrects issues in a print file without altering the original design to achieve a perfect part the first time it is printed.

Omar Fergani, Ph.D., co-founder and CEO of 1000 Kelvin, stated, “The manufacturing and production sector accounts for one-fifth of global carbon emissions and 54% of the world’s energy usage. 3D printing has the unique ability to address these issues, but not until it works consistently. By improving the efficiency and reducing the waste associated with 3D printing, while making the technology easier to use, AMAIZE contributes to a more sustainable future.”

This image displays the workflow for 1000 Kelvin’s software. Users upload a print file to the AMAIZE cloud, which analyzes the part and automatically corrects issues by modifying the printer’s instructions and recipe.

AMAIZE enables the generation of optimal print recipes using a physics-informed AI technology for first-time-right 3D printing. Users upload a print file to the AMAIZE cloud, which analyzes the part and automatically corrects thermo- mechanical issues by optimizing the scan strategy and process parameters. This eliminates the need for costly finite element simulation software and multiple physical iterations, which result in wasted materials, energy, and money.

1000 Kelvin has already directly integrated the cloud native solution AMAIZE with multiple machine OEMs enabling next generation AI- software and compute infrastructure for additive manufacturing. As a result of successfully concluding its early adoption program, AMAIZE has already been adopted by companies in the energy, aerospace, and contract manufacturing industries. One example is a California-based rocket launch provider, who faced significant challenges in 3D printing a critical part. The issues stemmed from print failure due to overheating and substantial reduction of support structures, leading to inefficiencies and delays.

By leveraging AMAIZE, the company was able to digitally iterate solutions to these thermal management problems. The result was a successfully printed part with improved surface quality and performance. Notably, AMAIZE enabled the customer to reduce support structures by over 80%, leading to a more than 30% reduction in the overall cost per part when considering both saved material and post-processing costs. This case study exemplifies how AMAIZE’s focus on tackling the root cause—thermal management—can significantly accelerate time to market.

1000 Kelvin has so far secured $3 million in funding, which has allowed it to grow beyond Europe and establish a presence in Los Angeles, CA to cater to its clients in the aerospace and defense industry.

About 1000 Kelvin

Founded by a team of former Siemens executives and experts in AI and additive manufacturing, 1000 Kelvin is committed to transforming the 3D printing industry. Its AI-driven software, AMAIZE, enables aerospace, medical, and industrial manufacturing companies to print metal parts ‘first-time-right,’ improving yield, quality, and repeatability while reducing costs and CO2 emissions.

For more information, please visit 1000Kelvin.com.

Singapore, Jan 9, 2024 – Chemical.AI recently announced a partnership with Nanyang Technological University, Singapore (NTU Singapore) to advance the automation progress in nanomaterials labs. Under this agreement, Chemical.AI will build the first automated research platform for NTU’s nanomaterials studies that enables synthesis, functionalization and measurement.

With integrated technologies of algorithms and equipment, Chemical.AI provides a fully automated and intelligent solution for nanomaterial synthesis, experimental process and analysis. Chemical.AI will also help NTU consolidate experimental data, establish databases of reaction conditions and results, and develop AI models to optimize reaction conditions for the synthesis of nanomaterials and to identify compound ingredients based on optical spectrum.

This collaboration is expected to significantly enhance the performance and efficiency of nanomaterial R&D by facilitating independent analysis of large experimental datasets, as well as making synthesis and measurement processes more intelligent. It sets a strong precedent for future explorations and research in novel materials.

“We are honored to start a long-term collaboration with NTU Singapore,” said Dr. Ning Xia, CEO of Chemical.AI. “Chemical.AI always aims to support chemists in various disciplines by optimizing lab productivity and accuracy. With our cutting-edge algorithms and profound lab experience, I’m confident that this platform will revolutionize novel material discovery and analysis.”

ChemAIoT, Chemical.AI’s self-developed AI + automation solutions for chemical lab, leverages over a decade of chemical informatics as its foundation and 60 million chemical big data as its backbone. It enables hybrid robots utilizing proprietary AI algorithms to achieve full-process automation and intelligence in chemical laboratories across various fields.

Designed to address real-world chemical lab needs and chemistry challenges, Chemical.AI algorithms can be utilized to customize reliable lab automation solutions and optimize lab module navigations. Each workstation carries out tasks autonomously and collaborates with other stations or a human researcher whenever needed. ChemAIoT is highly compatible with various third-party devices that can integrate with current laboratory equipment. It helps build the Internet of Things (IoT) and collect experimental data for AI modelling.

“NTU Singapore is committed to advancing research and development in nanomaterials, and we are excited to embrace digitalization and automation of our research work with Chemical.AI technology,” said Professor Xing Yi Ling from School of Chemistry, Chemical Engineering and Biotechnology. “With AI empowered syntheses and measurements, our scientists now have more time to concentrate on creative thinking, affording boundless possibilities for novel discoveries and expanded applications.”

About Chemical.AI

Founded in 2018, Chemical.AI leverages proprietary algorithms, comprehensive chemical data, and cutting-edge robotic lab automation to enhance chemical synthesis efficiency. With offices in Shanghai, Wuhan, Singapore, Boston, and Toronto, Chemical.AI has a team of 150 multidisciplinary experts skilled in retrosynthetic planning, automation, and lab digitalization, coupled with a rich database of chemical information and algorithms to pave the way in delivering advanced solutions across diverse sectors such as pharmaceuticals, biomedicine, chemical engineering, and new materials.

For more information, visit website.

LAS VEGAS, NV, Jan 9, 2024 – Siemens and Amazon Web Services (AWS) are strengthening their partnership and making it easier for businesses of all sizes and industries to build and scale generative artificial intelligence (AI) applications. Domain experts in fields such as engineering and manufacturing, as well as logistics, insurance or banking will be able to create new and upgrade existing applications with the most advanced generative AI technology. To make this possible, Siemens is integrating Amazon Bedrock – a service that offers a choice of high-performing foundation models from leading AI companies via a single API, along with security, privacy, and responsible AI capabilities – with Mendix, the leading low-code platform that is part of the Siemens Xcelerator portfolio.

“By integrating Amazon Bedrock into our low-code platform, we are democratizing generative AI technology and empowering everyone to create the applications customers need to become more competitive, resilient, and sustainable,” said Roland Busch, CEO of Siemens. “Making smarter applications without programming expertise accelerates innovation and helps companies to tackle skilled labor shortages.”

“Together, AWS and Siemens are empowering companies worldwide to create new capabilities, solutions, and value with generative AI,” said Adam Selipsky, AWS CEO. “This partnership builds on our 10-year relationship with Siemens, giving customers across all industries the flexible, customizable, secure environment they need to take advantage of new opportunities with generative AI.”

The combination will enable customers to select the generative AI model that best suits their specific use case and quickly and securely incorporate that model into their applications. This will make their development simpler, faster, and more efficient. Previously, when developers wanted to integrate generative AI models, they had to obtain access credentials, and write specialized function code. With the new Mendix-Amazon Bedrock integration, this can now be done with just a few clicks. Teams can create smart, industry-hardened applications without dedicated programming knowledge and users can interact with information easily via a graphical interface and the simplicity of a drag and drop commands.

This innovation allows Mendix customers to apply generative AI to drive productivity within their workforce. For instance, using generative AI, a factory worker can find machine documentation faster, generating relevant visualizations without a need to manually search a database, manuals, and records. A production engineer could also use generative AI to suggest machine adjustments to improve yield, and get suggestions on equipment adjustments, maintenance, or even spare parts to maximize a factory’s productivity.  Customers do not need to build their own AI infrastructure and will be able to harness the power of their company’s data with the highest possible security and privacy, maintaining full control of their data.

Generative AI technology can supercharge applications with features like summarizing and analyzing lengthy technical or legal documents, translating content into different languages, or recognizing images. Financial businesses can integrate automatic fraud detection in their software, while workers in a car factory can improve quality based on AI analysis of millions of data points in the manufacturing line. With access to a choice of foundational models on Amazon Bedrock, users can easily select the best model for their specific task and integrate it with just a few clicks.

The collaboration expands on the long-established partnership between AWS and Siemens to help streamline the use of IT and cloud technology so it can be easily integrated in applications and machine workflows, making it seamless to engage with.

Today, more than 50 million end users worldwide work with more than 200,000 applications built with Mendix’s low-code platform, available as part of the Siemens Xcelerator portfolio. Low-code platforms are expected to grow substantially over the next years. The technology enables developers to create applications by drag and drop with reusable components and software building blocks, which means they can build more software faster and with smaller teams.

Amazon Bedrock is a fully managed service that offers easy access to a choice of industry-leading large language models and other foundation models from AI21 Labs, Amazon, Anthropic, Cohere, Meta, and Stability AI, along with a broad set of capabilities that customers need to build generative AI applications—simplifying development while supporting privacy and security.  Users can also apply Guardrails to filter undesired content, adhere to responsible AI policies, or finetune their models using Knowledge Bases for Amazon Bedrock to give contextual information from private data sources and more relevant, accurate, and customized responses. The Mendix-Amazon Bedrock integration complements AWS’s other generative AI services, like Amazon CodeWhisperer, a machine learning (ML)–powered service that helps improve developer productivity by generating code recommendations based on developers’ comments in natural language and their code.  Together, the services extend the benefits of generative AI to developers and enterprise users regardless of their programming abilities.

About Siemens AG 

Siemens AG (Berlin and Munich) is a leading technology company focused on industry, infrastructure, transport, and healthcare. From more resource-efficient factories, resilient supply chains, and smarter buildings and grids, to cleaner and more comfortable transportation as well as advanced healthcare, the company creates technology with purpose adding real value for customers. By combining the real and the digital worlds, Siemens empowers its customers to transform their industries and markets, helping them to transform the everyday for billions of people.

In fiscal 2023, which ended on September 30, 2023, the Siemens Group generated revenue of €77.8 billion and net income of €8.5 billion. As of September 30, 2023, the company employed around 320,000 people worldwide. Further information is available on the Internet at www.siemens.com.

SACRAMENTO, CA, Jan 3, 2023 – Clapself, a leading AI-powered talent platform, announced the launch of its AI Professionals service. Available immediately, this groundbreaking offering by Clapself provides businesses across industries swift access to exceptional AI talent.

Artificial Intelligence is fast transforming industries. As per a PwC report, 70% of businesses are involved with AI in some way. “Securing specialized talent is critical for businesses to thrive. Acknowledging this growing demand, Clapself proudly introduces its AI Talent services—an exclusive gateway to a pool of top-tier, pre-vetted AI tech professionals,” said Bryan Verduzco, co-founder and chief growth officer of Clapself.

Key Features of Clapself AI Talent Service:

1. Rapid Deployment: A pre-vetted pool of AI talent ready for immediate deployment.
2. Specialized Expertise: Experts in Machine Learning, Natural Language Processing, Computer Vision, and other specialized domains.
3. Cost-Efficiency: Need based deployment, without the overheads of permanent hires.
4. Speed to Market: Accelerated development and reduced time-to-market for AI-powered offerings.
5. Custom: Flexibility to scale up or down based on project requirements.

According to MarketsandMarkets, the global Artificial Intelligence market is expected to grow at a CAGR of 36.8% to reach USD 1.3T by 2030 from USD 150.2B in 2023. As more organizations are recognizing the transformative potential of AI/ML to improve operational efficiency, enhance customer experiences, and drive innovation, the demand for AI skills such as Machine Learning, Natural Language Processing, Computer Vision, and Predictive Analytics has reached unprecedented levels.

“Clapself uses AI to connect customers with the top talent, for meeting project specific needs,” said Ramna Sharma, founder and president of Clapself.

Dave Sanders, chief mentor at Clapself acknowledged the increased demand for the unique AI skillset. “Clapself is well poised to lead the effort to identify and connect with some of the leading experts in this field, providing their clients a competitive advantage to access these limited resources,” he added.

About Clapself, Inc.

Clapself is an AI-powered talent platform where tech professionals engage with enterprises for mutual impact and benefit. The mission of Clapself is to help professionals and enterprises thrive in the new era of work. Headquartered in Sacramento, CA, Clapself is a virtual-first organization.

To learn more, visit website.