Bezos Expeditions manages Jeff Bezos' personal venture capital investments.

Bezos Expeditions

SoftBank provides fixed-line, mobile telephony, internet, telecommunications, and digital television products. It is a multinational telecommunications and internet corporation focused on broadband, fixed-line telecommunications, e-commerce, the internet, technology services, finance, media and marketing, and other businesses. The company operates through four segments. The mobile communications segment provides mobile communications services, produces and distributes online games for smartphones and other devices, offers mobile broadband services, provides supply chain solutions, handset protection, and insurance, buy-back and trade-in services, omnichannel solutions, and financial services, and sells mobile devices such as iPhones, iPads, and SoftBank smartphones. The Sprint segment offers mobile and fixed-line voice and data transmission services for individual consumers, businesses, government subscribers, and resellers in Puerto Rico and the U.S. and sells mobile devices and accessories. The fixed-line telecommunications segment offers telecom services such as fixed-line telephone and data communications services to corporate customers and broadband services to individual customers. The internet segment is engaged in the operation of the Yahoo! Japan portal, the sale of internet advertising, the operation of e-commerce sites, the provision of membership services, the sale and marketing of data centers, the provision of online automobile-related information, and the operation of the internet affiliate system. SoftBank also generates and sells electricity from renewable energy sources; provides payment processing, invoice collections, and computation services for businesses; distributes video, voice, and data content via media; operates the IT information site ITmedia; provides solutions and services for online businesses; and operates online games and software downloads. Additionally, it is involved in the ownership of professional baseball teams, the operation of baseball games, the management and maintenance of baseball stadiums and other sports facilities, and the procurement of funds by issuing preferred securities.

SoftBank

Coatue is a privately owned hedge fund sponsor. The firm invests in the public equity markets globally focusing on investments in technology, media, and telecommunications in addition to other sectors. It employs a long or short strategy to make its investments.

Coatue

Lightspeed Venture Partners is a venture capital firm that engages in consumer, enterprise, technology, and cleantech markets. It focuses on seed, early-stage, later-stage, expansion-stage, start-ups, growth companies, and incubation, and specializes in debt financing for start-ups and growth companies. Lightspeed Venture Partners invests in various sectors that include enterprise, consumer, big data, bitcoin, enterprise technology, cleantech, mobile, internet, financial technology, cloud solutions, e-commerce, storage, media, networking, energy, and software, software-as-a-service, information technology, biotechnology, and social. It mainly invests in countries such as the United States, Europe, Israel, China, and India.

Lightspeed Venture Partners

Sequoia is a venture capital focused on energy, financial, enterprise, healthcare, internet, and mobile startups. The firm helps a small number of daring founders build legendary companies. It spurs them to push the boundaries of what’s possible. The firm seeks to invest in all sectors with a focus on energy, financials and financial services, healthcare and healthcare services, Internet, mobile, outsourcing, and technology.

Sequoia Capital

Menlo Ventures provides capital for multi-stage consumer, enterprise, and life sciences technology companies. Since 1976, the firm’s market-driven analysis has led to the identification of opportunities and successful investments in innovative markets. Notable areas of investment include Marketplaces (Uber, Rover.com, Poshmark); Consumer Services (Tumblr, Betterment, Roku, Siri); Dev/Ops (Harness, Edge Delta, Fire hydrant); SaaS (Carta, ScoutRFP, Qualia, Benchling, Everlaw); Fintech (Betterment, Bluevine, Chime); Cybersecurity (Cavium, IronPort, BitSight, Abnormal, StackRox); and Life Sciences Technology (Synthego, Cofactor Genomics, Recursion Pharmaceuticals, 3T Biosciences). Menlo’s portfolio includes more than 70 public companies, and more than 100 mergers and acquisitions, with $5 billion under management. The firm is currently investing in Menlo Ventures XV, a $500 million early-stage fund, as well as its $500 million Inflection Fund, which targets early-growth investments.

Menlo Ventures

Felicis Ventures is a venture capital firm based in Menlo Park, California. The firm invests in seed through Series C stage companies across multiple sectors and industries reinventing core markets, as well as those creating frontier technologies. Felicis currently manages over $2B in capital across 8 funds. The firm is an early backer of more than 40 companies valued at $1B+. More than 90 of its portfolio companies have been acquired or gone public since the firm was founded by Aydin Senkut in 2006.

Felicis

General Catalyst is a venture capital firm that provides early-stage and growth equity investments. The company provides ongoing momentum that accelerates ideas, careers, and companies toward standout success.

General Catalyst

SV Angel is a San Francisco-based venture fund. Their experience spans helping companies like Airbnb, Coinbase, Databricks, DoorDash, Faire, Flexport, GitHub, Notion, Pinterest, Snap, Square, and Stripe Scale. Over the last 30 years of investing, their core values of trust, loyalty, and integrity along with a founder-first approach have driven our strategy. They are a service organization, investing in founders who share these values. They support entrepreneurs in building lasting companies by assisting at key inflection points and leveraging networks to help them propel their businesses forward.

SV Angel

Carnegie Mellon University is a global research university with more than 11,000 students, 84,000 alumni, and 4,000 faculty and staff. Recognized for its world-class arts and technology programs, collaboration across disciplines, and innovative leadership in education, Carnegie Mellon is consistently a top-ranked university.

Carnegie Mellon University

Amazon operates a vast online marketplace where customers can purchase a wide variety of products, including electronics, books, apparel, household goods, and more. The company has a robust logistics and delivery network, allowing for efficient shipping and quick delivery times for customers.

Amazon

The Amazon Alexa Fund is Amazon’s venture capital fund investing in artificial intelligence, frontier tech, voice, robotics, and digital health across consumer and enterprise. We invest in early- to growth-stage companies globally. To learn more, visit us at alexafund.com.

Amazon Alexa Fund

CRV has been an investor in technology companies for almost half a century. The firm has backed nearly 400 startups in its 47-year history, including foundational companies like Twitter, Zendesk, Amgen, Hubspot, Parametric Technologies, Yammer, EqualLogic, and Sonus Networks. Half of the companies CRV has backed have gone public or been acquired. The firm focuses on enterprise, consumer, and deep-insight bioengineering. CRV has offices in Palo Alto, California, and Cambridge, Massachusetts.

The Amazon Industrial Innovation Fund is a $1 billion corporate venture capital fund that supports emerging technology companies through direct investments.

Amazon Industrial Innovation Fund

Skild AI

Skild AI is a startup that develops software to power various robots including ones with two or four legs.

Skild AI is developing a scalable artificial intelligence foundation model for robotics. The company's goal is to create a shared, general-purpose AI "brain" that can be applied to various types of robots, enabling them to perform diverse tasks such as manipulation, locomotion, and navigation across different environments. Skild AI's model is trained on significantly more data points than competing models, allowing for greater generalization and emergent capabilities. The company aims to make robots more agile, dexterous, and safe for human interaction, potentially expanding their use in industries facing labor shortages such as healthcare, construction, warehousing, and manufacturing.

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Skild AI grabs $300M to build foundation model for robotics

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Revolutionizing efficiency by redefining human interactions

Humanoid Robots

Skild AI offers foundational models that can be integrated into various robots, enabling them to perform tasks such as climbing steep slopes, navigating around obstacles, and identifying and picking up objects. The models can be used for various robot scenarios and applications involving manipulation, locomotion, and navigation. The company aims to develop low-cost robots for tasks such as inspection, surveillance, and manipulation in household and industrial settings.

Foundation Models

The 10 Biggest Rounds Of July: Skild AI And Element Biosciences Lead Hot Month

Skild AI is developing a scalable artificial intelligence foundation model for robotics. The company's goal is to create a shared, general-purpose AI "brain" that can be applied to various types of robots, enabling them to perform diverse tasks such as manipulation, locomotion, and navigation across different environments. Skild AI's model is trained on significantly more data points than competing models, allowing for greater generalization and emergent capabilities. The company aims to make robots more agile, dexterous, and safe for human interaction, potentially expanding their use in industries facing labor shortages such as healthcare, construction, warehousing, and manufacturing.

UBTech Robotics is a Shenzhen-based company that manufactures humanoid robots for various applications. UBTech's product lineup includes educational robots, logistics robots, and intelligent service robots customized for specific industries like manufacturing and healthcare.Their humanoid robots are equipped with capabilities like sensing, voice interaction, navigation, greeting visitors, and performing tasks such as walking and grasping objects. Key products include the Alpha small humanoid launched in 2014, the Walker humanoid service robot introduced in 2018 for general services, and the upgraded Walker X released in 2021.

UBTech Robotics

Figure is a robotics startup founded with the goal of developing the world's first commercially viable general-purpose humanoid robot called Figure 01. The company is led by CEO Brett Adcock and CTO Jerry Pratt, a renowned roboticist who previously worked at the Florida Institute for Human and Machine Cognition (IHMC).
Figure one is designed to mimic the human form, standing five feet six inches tall, weighing 130 pounds, and capable of lifting up to 44 pounds. It features 41 degrees of freedom, including seven in each arm, six in each leg, and a six degree-of-freedom hand with an opposable thumb. The robot is fully electric, running for five hours on a single charge.
Figure one aims to address labor shortages by assisting human workers in manufacturing, logistics, warehousing, and retail settings. It leverages advanced AI and machine learning capabilities to perform tasks autonomously, enabling it to navigate complex environments, grasp objects, and manipulate tools. In March 2024, Figure demonstrated the robot handling warehouse tasks such as picking up bins and placing them on a conveyor belt.
Key customers and partnerships
In January 2024, Figure announced a commercial agreement with BMW to deploy its robots on the automaker's production lines.
Figure has also entered a collaboration with OpenAI to develop next-generation AI models specifically for humanoid robots. This partnership aims to enhance Figure 01's ability to process and reason from language, accelerating its commercial deployment timeline.

Figure

Agile Robots AG is a robotics company founded as a spin-off from the German Aerospace Center (DLR). The company's mission is to bridge the gap between artificial intelligence (AI) and robotics by developing systems that combine state-of-the-art force-moment sensing and world-leading image processing technology. This unique combination enables Agile Robots to provide intelligent, user-friendly, and affordable robotic solutions that facilitate safe human-robot interaction.
Agile Robots offers a range of robotic arms for industrial applications as well as research and educational purposes. Their product portfolio includes industrial robot arms, collaborative robot (cobot) arms, robotic software, an anthropomorphic robotic hand, and an educational platform called Aini that teaches foundational concepts in logic, computer science, mathematics, and physics by enabling students aged eight to 15 to program and operate robots.
In November 2023, Agile Robots acquired Franka Emika GmbH, a German robotics company known for its Panda collaborative robot arm. The acquisition, valued at over 30 million euros, allowed Agile Robots to expand its operations, retain Franka Emika's 100-person workforce, and strengthen its position in the robotics industry.
As of November 2022, Agile Robots had over 1,000 employees worldwide. The company established a production facility in Kaufbeuren, Germany, with plans to hire an additional 60 employees and manufacture 2,500 robots per year within a few years.
Key customers and partnerships
In October 2023, Agile Robots gained idealworks, a subsidiary of the BMW Group focused on industrial automation, as a majority shareholder through a Series A financing round. This strategic partnership enables the joint development of new solutions and technologies, as well as access to further branches and markets. Agile Robots and idealworks complement each other in their industry expertise and range of solutions, with idealworks bringing in the BMW Group as one of its largest customers and its industrial know-how.

Agile Robots

SoftBank Robotics is a leading provider of robotic solutions for various industries, including food service, cleaning, and logistics. The company's core offerings include autonomous cleaning robots like the Whiz series and Scrubber 50 Pro, tray delivery robots such as Servi, Keenbot T5, and Delivery X1, as well as logistics automation solutions leveraging technologies like AutoStore's high-density automated warehousing system.
SoftBank Robotics' cleaning robots, powered by artificial intelligence, can efficiently clean and disinfect floors while detecting and removing stains. The tray delivery robots are designed to optimize operations in the food service industry, reducing staff workload by autonomously transporting food and drinks between tables and the kitchen. The company's logistics solutions aim to optimize warehouse operations by maximizing space utilization and enabling efficient storage and retrieval of goods.

SoftBank Robotics

Agility Robotics is a company that develops and manufactures bipedal robots for industrial and commercial applications. Its flagship product is Digit, a human-sized bipedal robot designed to perform tasks such as moving heavy materials, picking up and putting down objects, and navigating through human-centric environments like warehouses and factories.
Digit is built on the principles of the spring-mass model, which replicates the dynamics of animal gaits to achieve efficient and natural bipedal locomotion. The robot's legs are modeled after an ostrich's, with a short thigh segment and long lower legs, enabling it to walk and run with remarkable energy economy. Digit is equipped with sensors and perception systems that allow it to operate autonomously or with human guidance.
Agility Robotics' technology has its roots in research conducted at Oregon State University, where the company was spun out in 2015. The company's early work focused on developing the ATRIAS and Cassie robots, which demonstrated the feasibility of using the spring-mass model for bipedal locomotion. Building on this research, Agility Robotics has commercialized the technology through Digit, which it began mass-producing in 2023.

Agility Robotics

Companies that develop full humanoid robots for research and education purposes in various fields such as science, technology, and academia

Companies that develop full humanoid robots for personal support and caregiving to assist individuals in their homes with tasks like cleaning, cooking, and providing companionship; includes applications in the medical and healthcare industry, such as assisting with surgeries, rehabilitation, or acting as companions for patients

Companies that develop full humanoid robots for entertainment purposes and social interaction. They can be used in public spaces, events, or as personal companions

Companies that develop full humanoid robots for commercial services across various industries such as retail, hospitality, and customer service

Companies that develop full humanoid robots for industrial and manufacturing settings to perform tasks such as assembly, material handling, and quality control

Companies that develop software and hardware that enable humanoid robot technology (e.g., sensors, grippers, cognitive architecture, robotic applications/software, etc.)

Uses IoT, AI/ML, and robotics to mimic human actions, kinesthetics, and mental state

Most of the companies in the industry use robotics technology to develop humanoid robots

Skild AI offers foundational models that can be integrated into various robots, enabling them to perform tasks such as climbing steep slopes, navigating around obstacles, and identifying and picking up objects. The models can be used for various robot scenarios and applications involving manipulation, locomotion, and navigation. The company aims to develop low-cost robots for tasks such as inspection, surveillance, and manipulation in household and industrial settings.Skild AI's model is reportedly trained on a database of text, images, and videos claimed to be 1,000 times larger than those used by competitors.Its foundational AI model serves as a shared, general-purpose brain for diverse robot embodiments across various tasks and environments.Key competitors: None comparable (No comparable companies in coverage that offers models targeting robot scenarios and applications involving manipulation, locomotion, and navigation)

<div>
 
 AI21 is an Israel-based AI research lab developing large language models (LLMs). The firm also builds GenAI applications based on its LLMs, marketing them to businesses and consumers.&nbsp;
 
 
 AI21 launched its first AI model, &ldquo;Jurassic-1,&rdquo; in August 2021, offering two versions. The larger variant, Jurassic-1 Jumbo, contained 178 billion parameters&mdash;three billion more than OpenAI&rsquo;s 175-billion parameter GPT-3 model. Similar to GPT-3, Jurassic is able to write emails and articles, summarize text, compose poetry and recipes, create website layouts, and generate code.&nbsp;
 
 
 The firm concurrently launched AI21 Studio, a platform allowing users to train custom versions of Jurassic-1 and embed them into products via an API.&nbsp;
 
 
 In May 2022, AI21 confirmed it was working on a new AI system, called the &ldquo;modular reasoning knowledge and language&rdquo; or &ldquo;MRKL&rdquo; framework (pronounced &ldquo;miracle&rdquo;). MRKL augments LLMs, connecting to external sources and symbolic reasoning models to enable the generation of accurate historical information, news on current events, and dynamic information, such as weather, exchange rates, and Wikipedia information. This allows models to accurately answer math queries by calling a calculator and navigate more complex questions by breaking down queries into parts. An initial implementation of MRKL, Jurassic-X, is available on AI21 Studio, which allows users to connect LLMs to their own databases and navigate their data using natural language.
 
 
 In March 2023, the firm launched &ldquo;Jurassic-2,&rdquo; a successor to its initial language model. The new LLM differs from Jurassic-1 and most popular LLMs, in that it incorporates semantic reasoning into its text generation processes alongside statistical inference, enabling the model to more reliably and accurately respond to queries.
 
 
 AI21 says this was achieved by training Jurassic-2 in two phases: A traditional self-supervised phase using an extensive corpus of unstructured and unlabeled data and a second phase, involving a large volume of labeled data to teach the model to follow instructions. Jurassic-2 did not initially implement the MRKL framework, although AI21 confirmed it as an upcoming feature.
 
 
 The company claims that its foundation models are 30% more efficient than those of other providers and it also does not charge additional fees for the use of fine-tuned models.
 
 
 
 
 In March 2024,
 <a href="https://sp-edge.com/updates/27995">
 AI21 launched Jamba,
 </a>
 a model that integrates the Mamba Structured State Space model (SSM) technology and transformer components. The company further introduced 
 <a href="https://sp-edge.com/updates/32879">
 Jamba 1.5 Mini and Jamba 1.5 Large
 </a>
 to offer high performance and efficiency for long-context language processing in August 2024. The models have a hybrid architecture combining Transformer and Mamba approaches, allowing for quality responses with large context windows.
 
 
 Key customers and partnerships
 
 
 As of June 2023, AI21&rsquo;s customers include Latitude, Easyway, Verb, Tweet Hunter, and Harambee.
 
</div>

AI21 Labs

UK-based Stability AI is actively involved in building AI applications and offers a range of foundation models, including:Text-to-image modelStable Diffusion (SDXL 1.0): The open-source text-to-image model incorporates a dual network architecture with a 3.5-billion parameter base model and a 6.6-billion parameter refiner. The model was trained on image-caption pairs from the LAION-5B dataset derived from Common Crawl data. It excels in high-quality image generation, spatial object positioning, and complex concept recognition. The model can be fine-tuned for specific tasks using techniques such as embeddings, hypernetworks, and tools like DreamBooth, a deep-learning generation model.<a href="https://sp-edge.com/updates/30420">Stable Diffusion 3 Medium:</a> a text-to-image open-source AI models with 2 billion parameters utilizing a Diffusion Transformer Architecture and can be fine-tuned using small datasets.<a href="https://sp-edge.com/updates/32260">Stable Fast 3D:</a> Text-to-image model generates 3D images from a single 2D image.In November 2023, the company launched <a href="https://sp-edge.com/updates/23352">two new products</a> Sky Replacer and Stable 3D. Sky Replacer lets users manipulate the aesthetic of the sky in their photos from a choice of nine alternatives, enhancing the overall image appeal and Stable 3D aims to simplify the process of creating textured 3D objects, from images or text prompts, into a quick, automatic activity.Text-to-text modelsStable Beluga 1: The instruction-following language model is based on LLaMA 65 billion and has reasoning capabilities.Stable Beluga 2 (FreeWilly): An expansion to Stable Beluga 1, this model is based on LLaMA 70 billion and reportedly ranks near the top of the Open LLM Leaderboard.StableLM is an open-source language model suite; the company has released alpha versions of three billion- and seven-billion parameter models, with 15 to 65 billion-parameter models to follow. It's designed to generate text and code, and can power various downstream applications. <a href="https://sp-edge.com/updates/25750">Stable LM 2 1.6B, </a>an AI language model designed for multiple languages, was released in January 2024.The Japanese StableLM Alpha, is a seven-billion parameter Japanese language model, which claims to have superior performance compared to other publicly available Japanese language models. It offers text generation capabilities and is released under the Apache License 2.0 for commercial use, with an additional research version available for research purposes.StableCode has three billion parameters and is specifically designed to help programmers with coding tasks by providing autocomplete suggestions and responses to programming instructions.Text-to-audio modelStable Audio, which has 907 million parameters, uses a latent diffusion model architecture for audio and is conditioned on various factors including text metadata, audio file duration, and start time. This conditioning allows control over the content and length of the generated audio.Text-to-image model<a href="https://sp-edge.com/updates/26910">Stable Diffusion 3,</a> which has 800 million range and 8 billion parameters and combines a diffusion transformer architecture and flow matching. Additionally, the model can depict multi-subject prompts, create images, and correct spelling. <a href="https://sp-edge.com/updates/30068">Public preview</a> of this model was announced in June 2024.<a href="https://sp-edge.com/updates/26645">Stable Cascade,</a> a text-to-image model developed with a three-phase approach for image creation and modification.Text-to-video model<a href="https://sp-edge.com/updates/24289">Stable Video Diffusion</a>, an AI model designed to produce videos from images, offered as a research preview. The models, SVD and SVD-XT, can generate short, high-quality clips but come with limitations.<a href="https://sp-edge.com/updates/27695">Stable Video 3D (SV3D), </a>a GenAI tool to create 3D videos to create multi-view 3D models from a single input image and can produce short video content from image or text prompts.<a href="https://sp-edge.com/updates/31945">Stable Video 4D,</a> a model that enables users to upload video and obtain dynamic videos from different views.There has been considerable debate about the ethical and copyright implications of using stable diffusion to create images. The model is particularly permissive when it comes to creating different types of content, which has raised concerns about its potential for abuse. In response to its permissiveness, Stability AI has become involved in copyright infringement lawsuits, with artists and Getty Images raising legal objections to the use of their content in the model's training data.In March 2024, <a href="https://sp-edge.com/updates/27872">Stability AI's founder and CEO, Emad Mostaque, resigned from his role </a>and the company's board to focus on the development of decentralized AI to bring transparency and competitiveness to AI.In April 2024, the company made Stable Diffusion 3 and Stable Diffusion 3 Turbo available on the <a href="https://sp-edge.com/updates/28612">Stability AI developer platform API.</a>In May 2024, Stability AI <a href="https://sp-edge.com/updates/29321">introduced Stable Artisan,</a> a tool to enable media generation for Discord users.Key customers and partnershipsIn December 2022, Stability AI entered a partnership with Amazon, with AWS designated as the preferred cloud provider to facilitate the development and expansion of Stability AI's AI models.In March 2024,<a href="https://sp-edge.com/updates/27403"> Stability AI partnered with Tripo AI,</a> a provider of AI 3D models, to release TripoSR for 3D object reconstruction to cater to the demands of entertainment, gaming, industrial design, and architecture professionals, with responsive outputs for visualizing detailed 3D objects.In April 2024, the company<a href="https://sp-edge.com/updates/28612"> partnered with Fireworks AI,</a> a provider of API platforms, to deliver Stable Diffusion 3 and Stable Diffusion 3 Turbo for enterprises.In September 2024, the company <a href="https://sp-edge.com/updates/33262">launched Stable Image Ultra, Stable Diffusion 3 Large, and Stable Image Core</a>, its text-to-image models on Amazon Bedrock.

Stability AI

Cohere is a Canadian startup founded in 2019 by Aidan Gomez, Ivan Zhang, and Nick Frosst, with backgrounds in natural language processing and prior experience at Google Brain. The firm specializes in the development and deployment of large language models (LLMs) for various applications across enterprise and business use cases. Its foundation model, Cohere Command, is a large natural language text generation model with 52.4 billion parameters, focused on task-oriented dialogue, creating summarization, copywriting, dialogue extraction, and question answering.&nbsp;Cohere also provides Cohere Embed, a model designed to generate vector embeddings that capture the essence of text, improving capabilities in search, content moderation, and intent recognition. These embeddings help empower Cohere's multilingual customizable models, which can be fine-tuned to cater to specific use cases and industries. Additionally, Cohere ensures secure deployment options, including private cloud solutions, for added data security and privacy. In November 2023, Cohere unveiled <a href="https://sp-edge.com/updates/23446">Embed V3</a> with advanced capabilities in matching documents to queries, increasing the efficiency of retrieval augmented generation, and reducing the operational costs of LLM applications. In February 2024, the company introduced <a href="https://sp-edge.com/updates/26583">Aya,</a> an open-source LLM that supports 101 languages.According to Stanford University's HELM benchmarks, Cohere's Command model ranks among the highest-performing models available.In March 2024,<a href="https://sp-edge.com/updates/27502"> Cohere released an advanced language model, “Command-R,</a>” for enterprises. The model offers improved performance on retrieval augmented generation (RAG) and tool usage, with longer context windows of up to 128,000 tokens.In April 2024, <a href="https://sp-edge.com/updates/28198">the company released an advanced language model, Command R+</a>, for business applications. The model offers enhanced retrieval augmented generation (RAG) with citation, supports 10 business languages, and automates workflows. Additionally, <a href="https://sp-edge.com/updates/28463">Cohere also released Rerank 3,</a> a model designed to enhance enterprise search and RAG systems. In the same month, <a href="https://sp-edge.com/updates/28509">the company also introduced a private beta for Cohere Compass,</a> a foundation embedding model designed to allow multi-aspect data indexing and searching, and also <a href="https://sp-edge.com/updates/28789">launched a toolkit available for developers to build AI applications</a> faster, offering production-ready applications that can be deployed across cloud providers, with enhanced security and customization options.In May 2024, Cohere introduced <a href="https://sp-edge.com/updates/29350">Command R Fine-Tuning</a> for enhanced performance for business application workload and<a href="https://sp-edge.com/updates/29761"> released Aya 23, </a>a multilingual language model capable of handling 23 languages,available in 8 billion and 35 billion parameters.Key customers and partnerships&nbsp;In November 2021, Cohere partnered with Google Cloud to leverage its infrastructure support and TPUs for product development and deployment. Cohere also partnered with other major cloud providers like AWS and Oracle.&nbsp;In March 2024,<a href="https://sp-edge.com/updates/27307"> Cohere partnered with consultancy firm Accenture</a> to integrate its Command model and retrieval augmented generation (RAG) capabilities to offer GenAI solutions for businesses.&nbsp;In April 2024, <a href="https://sp-edge.com/updates/28932">Cohere partnered with Amazon </a>to incorporate Command R+ and Command R to Amazon's cloud platform, Bedrock.In June 2024, the company<a href="https://sp-edge.com/updates/30492"> partnered with Borderless AI,</a> a provider of AI-powered HR solutions, to create tailored AI agents for HR tasks.&nbsp;The company entered into a <a href="https://sp-edge.com/updates/31052">strategic partnership with i-5O,</a> a provider of AI solutions for manufacturing, as part of Cohere's Startup Program and also partnered with <a href="https://sp-edge.com/updates/31590">Fujitsu</a> in July 2024 to develop a Japanese LLM.&nbsp;

Cohere

<div>
 
 Founded in 2022, Hippocratic AI is a healthcare-focused AI model developed by Health GPT. At its core, Hippocratic AI uses a state-of-the-art (SOTA) large language model (LLM) designed to improve healthcare processes, particularly in non-diagnostic tasks. Hippocratic AI aims to differentiate itself from traditional LLMs by prioritizing pre-training with trusted, evidence-based healthcare content rather than the broader Internet. Claimed to be the first safety-focused LLM for healthcare, the model undergoes a unique Reinforcement Learning with Human Feedback process, known as RLHF-HP, which involves working with healthcare professionals to validate its readiness for use. In addition, the model aims to incorporate a compassionate &ldquo;bedside manner&rdquo; in its interactions with patients, recognizing the impact of empathy on emotional wellbeing and health outcomes.
 
 
 According to the company, Hippocratic AI outperformed GPT-4 in majority of tests and certifications. Out of 114 evaluations, it outperformed GPT-4 in 105 cases, with a notable margin of +5% in 74 evaluations and +10% in 43 certifications.
 
 
 Key customers and partnerships&nbsp;
 
 
 In August 2023, the company launched the Hippocratic AI Founding Partner Program, an initiative through which the company collaborates with leading healthcare organizations to become founding partners and actively participate in the development and validation of Hippocratic AI's LLM and technology. The program includes establishing use cases, ensuring clinical and patient safety, and contributing to the advancement of healthcare-specific AI applications. In February 2024, these companies began 
 <a href="https://sp-edge.com/updates/27145">
 beta
 </a>
 testing their LLM for non-diagnostic applications in healthcare.
 
 
 In March 2024, 
 <a href="https://sp-edge.com/updates/27696">
 Hippocratic AI partnered with NVIDIA
 </a>
 to develop AI healthcare agents that have low-latency conversational interactions with patients.
 
 
 Funding and financials&nbsp;
 
 
 In March 2024, 
 <a href="https://sp-edge.com/updates/27694">
 the company raised USD 53 million
 </a>
 in a Series A funding round co-led by Premji Invest and General Catalyst to invest in Phase III safety tests of its LLM and further develop of products.
 
 
 
</div>

Hippocratic AI

<div>
 
 Founded in 2023, GenHealth.ai is a startup focused on advancing healthcare solutions through the use of GenAI. Its proprietary approach involves training a foundation transformer model, known as DOOG-E, on extensive healthcare data, including 50+ million of coded patient claims and clinical information. DOOG-E is a specialized Generative Pre-Trained Transformer (GPT) AI designed for healthcare applications, with 70 million parameters and one billion tokens. Unlike traditional large language models, DOOG-E is a large medical model (LMM) that uses medical events such as ICD, CPT, RxNorm, and LOINC codes as its &quot;language&quot; to predict future sequences of health events based on historical data.
 
 
 The company claims that its LMM, trained on medical data, is less prone to bias and hallucination compared to its GenAI, large language models (LLM), rendering it more dependable for healthcare applications.
 
 
 Funding and financials&nbsp;
 
 
 In July 2023, the company raised USD 13 million in early funding co-led by Craft Venture and Obvious Ventures. It planned to use the funds to support the development and expansion of its LMM for various healthcare applications, including risk adjustment, care management, and financial benchmarking.
 
 
 
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GenHealth

Foundation models that can handle a range of natural language processing (NLP) use cases. Typical tasks include generating summaries, translating, answering questions, and classifying text. These models typically use text inputs and generate text outputs.

Fine-tuned versions of large language models, which are focused on specific tasks and applications (e.g. code generation, medical event prediction, financial NLP tasks, etc). These are usually developed by training LLMs using custom data and also serve as foundation models that can be developed even further. These models typically use text inputs and can generate text and/or code outputs.

Foundation models that translate visual data based on features and contextual information identified during training. This enables models to interpret images and video, applying those interpretations to predictive or decision-making tasks. Typical tasks include image recognition and classification into categories. These models typically use image and/or video inputs and generate text outputs.

Foundation models that are trained to understand and work with two or more forms of input data (e.g., text and images) to solve problems and complete tasks using both natural language processing and computer vision. These models can also generate outputs across textual and visual modalities. Typical tasks include visual question answering, image captioning, and generating images based on text descriptions. These models typically use text and/or visual inputs and generate text and/or visual outputs.

Foundation models that use big data to suggest or recommend additional products to consumers. These models are designed to predict user-item interaction probabilities and provide recommendations to users. The models are trained to make these inferences based on historical data on customer interactions and non-interactions. These models typically use user features, item features and user interactions as inputs, and generate numeric values like ratings predictions and matching probabilities as outputs.

Foundation models that are capable of automatic speech recognition, transcription in multiple languages, and translation from these languages to English. These are sometimes referred to as audio models. These models typically use speech/audio as inputs and generate text outputs.

Foundation models that transform user text prompts into video clips.

Foundation models that generate music from text descriptions.

All companies within the space are building large AI models

Companies in this space leverage NLP to train LLMs

The hub exclusively covers companies that have built foundation models

All companies within the space can leverage their foundation models for generative AI applications

The technology enables the creation of personalized content

<div>
 
 Skild AI, an AI and robotics model provider, has successfully raised 300 million USD in a Series A funding round. Notable contributors include Lightspeed Venture Partners, SoftBank Group, Coatue, Felicis Ventures, Sequoia, Menlo Ventures, General Catalyst, CRV, Amazon, SV Angel, and Carnegie Mellon University. This has significantly increased the company's valuation, bringing it to a total of 1.5 billion USD.
 The funding will be utilized for business expansion purposes. The company aims to enhance its model, invest in the training of datasets, and increase its workforce in AI, robotics, engineering, operations, and security departments.
 The company primarily provides foundational models, which can be integrated into various robots. This enables robots to perform complex operations like climbing steep slopes, navigating obstacles, and identifying and picking up objects. The models can be applied in a range of robotic scenarios and applications, covering areas such as manipulation, locomotion, and navigation.
 
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Skild AI

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