The Scale Team

Today, Scale will sign onto the Biden-Harris Administration&rsquo;s voluntary commitments to ensure that AI is safe, secure, and trustworthy. These commitments are critical to the future of AI. The reality is that progress in frontier model capabilities must happen alongside progress in model evaluation and safety. This is not only the right thing to do, but practical. &ldquo;To advance our knowledge and understanding of large language models (LLMs)&ndash;and therefore advance their capabilities&ndash;we must understand their weaknesses as much as their strengths. It is imperative for the tech industry to take proactive measures like these given the rapid pace of technological development.&rdquo; &ndash;Alexandr Wang
The Scale team commends the White House&rsquo;s leadership in bringing together companies that are shaping the future of responsible AI development. America&rsquo;s continued technological leadership hinges on our ability to build and embrace the most cutting-edge AI across all sectors of our economy and government. This can only be achieved with collaboration between industry and government to create a broad understanding of the possibilities and limitations of the technology, so the benefits can be maximized and risks minimized.&nbsp;
Safe, secure, and trustworthy AI has always been at the core of Scale&rsquo;s mission. For more than seven years, we have built deep expertise in the entire lifecycle of developing, fine-tuning, and testing and evaluating AI. Our role as the data partner for the leading model developers has given us a unique vantage point across the AI ecosystem. It has allowed us to deeply understand the challenges that must be addressed, how various players across the industry are working to tackle them, and ultimately develop our own technology to test and evaluate LLMs.&nbsp;
As a pioneer in the AI space, Scale is at the forefront of defining what it means for an LLM to be trusted and safe.
<ul>
<li>Scale is committed to helping the broader AI community understand the benefits and safety risks and partnering with leading model builders to evaluate the safety of their models. Red teaming, in particular, is a core pillar of our approach to testing and evaluation. <a href="https://www.whitehouse.gov/briefing-room/statements-releases/2023/05/04/fact-sheet-biden-harris-administration-announces-new-actions-to-promote-responsible-ai-innovation-that-protects-americans-rights-and-safety/" target="_blank" rel="noopener noreferrer">As announced by the White House&rsquo;s Office of Science and Technology Policy</a>, Scale was selected to develop the platform to evaluate leading generative AI systems for the largest red teaming exercise, to date, at DEFCON 31.&nbsp;</li>
<li>Scale published a vision for <a href="https://scale.com/guides/test-and-evaluation-vision" target="_blank" rel="noopener noreferrer">testing and evaluation </a>and developed a platform to help establish a framework for an effective industry-wide approach, limit bias, and uphold the Responsible AI Principles, such as those outlined in the <a href="https://www.whitehouse.gov/ostp/ai-bill-of-rights/" target="_blank" rel="noopener noreferrer">Biden Administration&rsquo;s AI Bill of Rights</a>. Successful adherence to and execution of these commitments is contingent on robust foundation model testing and evaluation.&nbsp;</li>
<li>Scale is grateful to join fellow industry leaders making these voluntary commitments to ensure the responsible development of AI technology. As we forge ahead, the company is committed to working with the Administration and public, private, and civil society to provide recommendations for concrete steps that can be taken to build a robust framework to unlock safe, secure, and trustworthy AI globally.</li>
</ul>

Today, Scale will sign onto the Biden-Harris Administration’s voluntary commitments to ensure that AI is safe, secure, and trustworthy.

Our Commitment to Ensuring Safe, Secure, and Trustworthy AI

Our Commitments to Safe, Secure, and Trustworthy AI

Today, Scale is announcing our Test &amp; Evaluation offering for LLMs, which is already being leveraged by OpenAI, and is available in early access to select customers who are at the forefront of LLM development.
Since large language models broke into the public consciousness, the conversation has largely fallen into two categories: The exciting realm of new possibilities this technology can unlock, and the risks that could come from opening Pandora&rsquo;s box.&nbsp;
While many would like to paint these as two opposite ends of the spectrum, the reality is that progress in frontier model capabilities must happen alongside progress in model evaluation and safety. This is not only a moral imperative, but a practical one. In order to advance our knowledge and understanding of LLMs &ndash; and therefore advance their capabilities &ndash; we must understand their weaknesses as much as their strengths.&nbsp;
Various studies have found popular LLMs hallucinate or provide inaccurate information ranging anywhere from 20% to 52% of the time. As AI is increasingly being leveraged by <a href="https://www.nytimes.com/2023/07/19/business/google-artificial-intelligence-news-articles.html" target="_blank" rel="noopener noreferrer">newsrooms</a>, misinformation has the potential to sway global markets and global politics. Other issues like unqualified advice have the potential to lead to real-world harms, such as providing <a href="https://mwi.westpoint.edu/disinformation-in-the-age-of-chatgpt/#:~:text=A%20study%20that%20enticed%20ChatGPT,war%20in%20Ukraine%2C%20and%20school" target="_blank" rel="noopener noreferrer">false medical information</a>, feeding into <a href="https://www.washingtonpost.com/technology/2023/08/07/ai-eating-disorders-thinspo-anorexia-bulimia/" target="_blank" rel="noopener noreferrer">mental disorders</a>, and more. LLMs can even be tricked into writing <a href="https://www.axios.com/2023/08/08/ibm-researchers-trick-chatgpt-hacking" target="_blank" rel="noopener noreferrer">malicious code</a>, opening new vectors for cybersecurity attacks.&nbsp;
For AI to reach its full potential, it&rsquo;s critical the AI industry is working to address these known challenges in parallel with other advancements to their models.&nbsp;
<h2>Our Approach to Test &amp; Evaluation</h2>
At Scale, for more than 7 years we have built up deep expertise in the entire lifecycle of developing, fine-tuning, testing and evaluating AI models. Our role as the data partner for companies like OpenAI, Meta, Microsoft, and Anthropic have given us a purview across the ecosystem that no other company has. It has allowed us to deeply understand the common challenges that must be addressed, how various players across the industry are working to address them, and ultimately develop our own technology to effectively test and evaluate LLMs.&nbsp;
Today, there is no standard for test and evaluation (T&amp;E) in AI. Our leadership in this space is why in May, the&nbsp;<a href="https://www.whitehouse.gov/briefing-room/statements-releases/2023/05/04/fact-sheet-biden-harris-administration-announces-new-actions-to-promote-responsible-ai-innovation-that-protects-americans-rights-and-safety/" target="_blank" rel="noopener noreferrer">White House announced</a> Scale was selected to develop the T&amp;E platform for DEF CON&rsquo;s public evaluation of models built by Anthropic, Cohere, Google, Hugging Face, Meta, NVIDIA, OpenAI, and Stability.&nbsp;
We&rsquo;re excited to see the industry come together for this moment, but this is just one step in the right direction. That&rsquo;s why today, we are releasing our stance on Test &amp; Evaluation to help set the standard for what an effective T&amp;E approach looks like. Like other realms of cybersecurity, we need to share best practices and methodologies and learn from each other. The industry needs to create standards that companies can follow, and be held to. We hope this is just the start of more collaboration across the industry.&nbsp;
Whether you&rsquo;re a builder or buyer, we want to enable startups, enterprises, and government agencies to test and evaluate AI for safety and security. Scale&rsquo;s methodology for a robust T&amp;E process and ecosystem spans three key pillars:
<ol>
<li>Hybrid model evaluation &ndash; conducted through a combination of automated evaluations and human expert evaluations to assess model capability and helpfulness over time.</li>
<li>Hybrid red-teaming &ndash; in-depth targeting by human experts of specific harms and techniques where a model may be weak, in order to elicit undesirable behavior. This behavior can then be cataloged, added to an adversarial test set for future tracking, and patched via additional tuning.</li>
<li>T&amp;E ecosystem &ndash;&nbsp;the paradigm by which T&amp;E should be institutionally implemented. We view this as a question of localizing the necessary ecosystem components and interaction dynamics across four institutional stakeholder groups: Frontier model developers; government; enterprises; and third-party organizations</li>
</ol>
Within this approach, we break down what T&amp;E is, how to do it, and how to implement it within the broader ecosystem.&nbsp;
Read our full approach to <a href="https://scale.com/guides/test-and-evaluation-vision" target="_blank" rel="noopener noreferrer">Test &amp; Evaluation here</a>.&nbsp;
<h2>Our Test &amp; Evaluation Offering</h2>
Enabling effective and secure generative AI will require a comprehensive T&amp;E offering, encompassing model evaluation, monitoring, and red teaming, as demonstrated in our approach to Test and Evaluation.&nbsp;
That&rsquo;s why, today, we are excited to be expanding on our critical safety and evaluation work with leading model builders and announcing early access availability for Scale&rsquo;s first T&amp;E offering, which is already being leveraged by OpenAI for red teaming their models.&nbsp;
This offering will be available to select customers who are at the forefront of LLM development, as it is critical we work together to ensure we are keeping the AI community in mind as we build.&nbsp;
Key components of our offering include:&nbsp;
<ol>
<li>Continuous Evaluation - continuously evaluate and monitor the performance of your AI systems</li>
<li>Red Teaming - identify severe risks and vulnerabilities for AI systems</li>
<li>AI System Certification - certify AI applications for safety and capability</li>
</ol>
To learn more, please visit the <a href="https://scale.com/llm-test-evaluation" target="_blank" rel="noopener noreferrer">product page</a>.&nbsp;
Together, we hope to enable safe, secure AI for all.

Scale unveils Test & Evaluation for LLMs, adopted by OpenAI, now in early access for leading LLM developers.

Setting test and evaluation standards | Scale AI

Building Trust in AI: Our vision for test and evaluation

Chegg, Inc. (NYSE: CHGG), the leading student-first online learning company, announced today its partnership with Scale AI, a leader in delivering high-quality training data for AI applications, to develop a proprietary large language model (LLM) to provide a generative learning experience for Chegg subscribers.
Scale helps customer build <a href="https://scale.com/custom-llms">custom LLMs</a> for their highest priority business use cases. Chegg&rsquo;s LLM will be specifically trained in education, leveraging the data, proprietary content, and the 150,000 subject matter experts that are unique to Chegg, creating a personalized and significantly enhanced learning experience for Chegg Study and Chegg Study Pack subscribers.&nbsp;
&ldquo;This partnership will accelerate our ability to bring generative AI tools&mdash;built for personalized learning&mdash;to all Chegg students beginning now and continuing into 2024,&rdquo; said Dan Rosensweig, President and CEO of Chegg. &ldquo;Scale is a category leader in the AI space, and they have the proven ability to help organizations scale and reach their business objectives. We are excited about the future of this partnership, and how it will impact learners.&rdquo;&nbsp;
Over the past several months, Chegg and Scale tested a successful pilot of the AI experience for students. As part of the partnership, Chegg has named category exclusivity in the educational market. With Chegg&rsquo;s new learning experience, students can access new conversational and personalized learning pathways tailored to their individual learning styles.
&ldquo;The partnership with Scale will allow us to develop new AI and machine learning models unique to Chegg and help us accelerate the annotating and categorizing of data in order to make high-quality datasets and train our AI platforms while maintaining our own IP,&rdquo; said Nathan Schultz, Chief Operating Officer of Chegg.&nbsp;
&nbsp;
Read the <a href="https://www.businesswire.com/news/home/20230807741451/en/Chegg-Partners-with-Scale-AI-to-Enhance-Learning-Experience-for-Students">full press release.</a>
Looking to build your own custom LLM?&nbsp;<a href="https://scale.com/custom-llms">Learn mo</a><a href="https://scale.com/custom-llms">re</a>.

Scale helps customer build custom LLMs for their highest priority business use cases. Chegg’s LLM will be specifically trained in education, leveraging the data, proprietary content, and the 150,000 subject matter experts that are unique to Chegg, creating a personalized and significantly enhanced learning experience for Chegg Study and Chegg Study Pack subscribers. 

Chegg Partners with Scale AI to Build Custom LLMs for an Improved Learning Experience

Chegg Partners with Scale AI to Build Custom LLM for an Improved Learning Experience

Scale, the data infrastructure company for AI, is excited to announce that the Department of Defense (DoD) Chief Digital and Artificial Intelligence Office (CDAO) awarded us a new Other Transaction Agreement (OTA), a type of contract that will boost the DoD&rsquo;s efforts to advance artificial intelligence (AI) capabilities for the military.&nbsp;
This agreement with the CDAO will enable Scale to provide the Joint Force with data curation and annotation capabilities via Scale&rsquo;s <a href="https://scale.com/data-engine">Data Engine</a>. The capabilities will be made available across a diverse range of networks and classification levels relevant to warfighters.&nbsp;
Our partnership with the CDAO aims to build the robust AI infrastructure that is necessary to move AI pilots and prototypes out of labs and experimental environments into production for front-line teams. Moreover, the contract will help meet Combatant Commands&rsquo; crucial requirements for enhanced data to power machine learning algorithms. Notably, this capability will play a pivotal role in supporting multimodal data pipelines, such as full motion video, synthetic-aperture radar, and electro-optical imagery. We are excited to bring this capability to the Department of Defense and deploy Scale&rsquo;s suite of tools to both unclassified and classified workflows spanning projects across the Army, Marine Corps, Navy, Air Force, Space Force and Coast Guard.
Scale received the award via the CDAO&rsquo;s Tradewind Solutions Marketplace. This innovative digital repository of post-competition, readily-awardable solutions addresses the Government&rsquo;s greatest challenges in the AI/ML, digital, and data analytics space. Scale commends the CDAO and Tradewind for its partnership with commercial technology leaders to help the DoD achieve AI overmatch. At Scale, we are honored to be entrusted with this new agreement and look forward to contributing our expertise to the development of advanced AI capabilities for the DoD.
Learn more about Scale&rsquo;s Data Engine at <a href="https://scale.com/data-engine">https://scale.com/data-engine</a>, and verified .gov and .mil users can sign up for a 7-day trial of Donovan, our AI-powered decision-making platform here: <a href="https://scale.com/donovan-trial">https://scale.com/donovan-trial</a>
&nbsp;

Scale, the data infrastructure for AI, is excited to announce that the Department of Defense (DoD) Chief Digital and AI Office (CDAO) awarded us a new Other Transaction Agreement (OTA), a type of contract that will boost the DoD’s efforts to advance artificial intelligence (AI) capabilities for the military. 

Scale

Scale AI Awarded DoD Contract to Deliver Data Curation and Annotation Capabilities to Power AI Across the Joint Force

<a href="https://scale.com/">Scale AI</a>&nbsp;has been selected by the U.S. Army and the <a href="https://www.diu.mil/">Defense Innovation Unit</a> (DIU) to deploy their Data Engine in support of the Army&rsquo;s Robotic Combat Vehicle (RCV) program. The effort is a joint collaboration between DIU and the Army&rsquo;s Program Executive Office Ground Combat Systems (PEO GCS) leveraging innovative Other Transaction Authority for the novel application of Scale&rsquo;s commercial technology to the RCV program.
The Army has determined that the next stage of navigating high-risk environments requires advanced technology, like trusted autonomous systems, to safely conduct reconnaissance and related tasks. Scale will play a vital role in the development of these systems by providing its Data Engine platform to support raw data collection, curation, and labeling, as well as AI model development and test and evaluation for autonomous navigation software and computer vision algorithms.&nbsp;&nbsp;&nbsp;
Mitigating risk for combat troops is paramount in military operations, and Scale is committed to supporting the U.S. Army&rsquo;s efforts to ensure the safety of our service men and women. With a strong background in the autonomy space, Scale has established partnerships with notable customers such as General Motors, Lyft, and Toyota. Leveraging their deep expertise, Scale will provide robust support for the RCV program, delivering proven commercial technology tailored for defense applications, including off-road terrain, extreme weather conditions, and contested or degraded communications.
Whether you&rsquo;re a fighter pilot in the Air Force, or an Armor Officer in the Army, nothing replaces real world training events when developing combat-ready Airmen or Soldiers; synthetics and simulation can only get you so far and AI for autonomy is no different. Scale is excited to partner with the U.S. Army who will benefit from our deep expertise in autonomy combined with our <a href="https://scale.com/data-engine">Data Engine </a>technology, to deliver the data management plans and platforms DoD autonomy programs need.&nbsp;
Learn more here: <a href="https://scale.com/data-engine">https://scale.com/data-engine</a>
&nbsp;

Scale AI has been selected by the U.S. Army and the Defense Innovation Unit (DIU) to deploy their Data Engine in support of the Army’s (RCV) program. 

Scale AI chosen by the U.S. Army for Robotic Combat Vehicle Program

Generative AI is capturing the imaginations of consumers and businesses alike. However, in this early era of adoption, most enterprises are yet to unlock true impact from this technology and are stuck in the experimental stages. Some are concerned about the security of their data and the reliability of model outputs. Others are overwhelmed by the many decisions to make regarding foundation models, prompt strategies, and tooling for developers.&nbsp;
Scale and <a href="https://www.anthropic.com/" target="_blank" rel="noopener">Anthropic</a> are excited to announce our partnership to bring to market a full-stack solution for Generative AI applications&nbsp;with a focus on safety and responsibility. This collaboration enables customers to bring Generative AI applications to production and to capture business value from this incredible technology.&nbsp;
Our partnership combines <a href="https://www.anthropic.com/product" target="_blank" rel="noopener">Anthropic&rsquo;s Claude</a> &ndash; a large language model guided by principles with the goal of creating outputs that are more consistent with human intent and values &ndash; with <a href="https://scale.com/generative-ai-platform">Scale&rsquo;s enterprise-grade platform</a> for app experimentation, development, and deployment.&nbsp;&nbsp;
Customers will be able to make the most of Claude with Scale&rsquo;s offerings:
<ul>
<li dir="ltr" aria-level="1">
Expert prompt engineering to guide users with the right prompt strategies and pre-built prompt templates, plus the ability to run experiments with different prompts.
</li>
<li dir="ltr" aria-level="1">
Data connectors to leverage proprietary data from databases and applications such as Confluence, Google Drive, Outlook, etc.
</li>
<li dir="ltr" aria-level="1">
Model validation through human evaluation to understand model blind spots and improve model performance, and features to continuously measure accuracy, brand alignment, and safety metrics, including sensitive content detection tailored to customers&rsquo; policies and brand.
</li>
<li dir="ltr" aria-level="1">
Enterprise-grade privacy and security, including deployment in a customer&rsquo;s AWS VPC and role-based access controls to ensure data and outputs are limited to the appropriate groups.
</li>
</ul>
Scale and Anthropic believe this represents a significant step forward for enterprises seeking to rapidly move beyond experimentation with Generative AI models. Designed to address concerns around data security, and model performance and reliability, this collaboration provides an accessible, &ldquo;all-in-one&rdquo; approach for customers to confidently tap into the power of Generative AI.

Scale and Anthropic are excited to announce our partnership to bring to market a full-stack solution for Generative AI applications, with a focus on safety and responsibility. This collaboration enables customers to bring Generative AI applications to production and to capture business value from this incredible technology. 

Scale + Anthropic: Full-Stack Generative AI for Enterprises | Scale AI

Scale + Anthropic: Full-Stack Generative AI for Enterprises

Artificial Intelligence (AI) has been a game-changer for everyone. Together with data, AI has become a key component of a robust digital core&mdash;the main source of competitive advantage for companies today. The advent of&nbsp;<a href="https://www.accenture.com/us-en/insights/technology/generative-ai" data-analytics-link-name="generative ai" data-analytics-content-type="cta">generative AI</a>&nbsp;marks the beginning of a new era, one where businesses&nbsp;<a href="https://www.accenture.com/us-en/insights/consulting/total-enterprise-reinvention" data-analytics-link-name="reinvent" data-analytics-content-type="cta">reinvent</a>&nbsp;how they work. Just search for ChatGPT if you haven&rsquo;t already, and you&rsquo;ll get an idea of the possibilities. ChatGPT is derived from a large language model (LLM)&mdash;GPT4&mdash;developed by Open AI, which is a foundation model capable of generating human-like language and carrying out complex tasks across a number of functions.
We are entering an era of AI industrialization, where entire industries stand to be transformed by new, innovative applications of generative AI. One of the highest barriers to unlocking business value using generative AI and LLMs, however, is customizing and fine-tuning the pre-trained foundation models for their unique needs, using their own data. That&rsquo;s why Accenture is partnering with Scale AI.&nbsp;
<a title="Scale AI &amp; Accenture Partnership" href="https://scaleai.wistia.com/medias/2fjp89kejj">video</a>
&nbsp;
<h3 class="p1">Generative AI partner spotlight: Scale AI</h3>
Accenture&rsquo;s collaboration with&nbsp;<a href="https://scale.com/" target="_blank" rel="noopener" data-analytics-link-name="scale ai" data-analytics-content-type="cta">Scale AI</a>&nbsp;focuses on helping enterprises use their own data on general purpose models, customizing them to suit their business needs. According to CEO and founder Alexandr Wang, Scale AI has been &ldquo;quietly powering this generative AI wave, providing the data and infrastructure for many of the top companies to actually build large-scale foundation models, including Open AI.&rdquo;
Accenture and Scale AI are collaborating to provide an enterprise LLM platform for enterprise and government clients to fine-tune generative AI models that can learn from human input through a process called Reinforcement Learning from Human Feedback (RLHF). The result is generative models optimized for human interaction that are able to improve how people live and work.
For example, Scale AI was able to help retail clients gain higher shopping conversion and sales by using AI-generated product images for their newest products. And with social media clients, AI-generated content led to more than 100 million impressions.
Could humans have done this? Absolutely &ndash; but at what cost to the business?
This is business augmentation at the intersection of human and machine. By freeing up employees from automatable, routine tasks, we can redirect energy and focus to more strategic creative work that requires human intuition, decision-making and problem-solving skills - work that generative AI cannot do&mdash;at least not yet. The combination of human plus machine results in more efficient processes, improved decision-making and greater innovation.
Success with generative AI depends as much on people and training as it does on technology. It&rsquo;s up to business leaders to take the lead in upskilling employees and reshaping jobs and tasks to get the most out of technologies like generative AI.
Thanks to partnerships like this one with Scale AI, Accenture helps leaders create business value with generative AI technology quickly and at scale.

Scale AI + Accenture: Enhancing Business Value with Human Ingenuity

Scale AI, the data infrastructure for AI, has been named a Cool Vendor in the 2022 <a href="https://www.gartner.com/doc/reprints?id=1-2C7YMC4Z&amp;ct=230109&amp;st=sb">Gartner Cool Vendors&trade; in Data-Centric AI</a> by Svetlana Sicular, Arun Chandrasekaran, Sumit Agarwal, Oleksandr Matvitskyy and Anthony Mullen.
The biggest barriers for organizations looking to implement data-centric AI strategies are having the necessary resources, talent, experience and high-quality data needed to feed algorithms and leverage the power of AI. Scale provides AI solutions tailored to business use cases and machine learning tools to unlock breakthroughs like Generative AI and operationalize AI for all organizations spanning the U.S. government, researchers, startups and Fortune 500 companies across e-commerce, logistics, technology, fintech, and more industries. Organizations such as Microsoft, Open AI, SAP, Flexport and the U.S. Army partner with Scale to solve problems with data labeling and annotation, scenario-based model testing and validation, ​​content understanding and contextualization, AI catalog for asset reusability and more.
According to Gartner, &ldquo;Data challenges plague AI implementations. They are often unexpected because AI teams focus on algorithms, and data concerns come as an afterthought.&rdquo; It recommends that when evaluating data-centric AI solutions, organizations should &ldquo;work with stakeholders to determine what data characteristics are high value for AI,&rdquo; and &ldquo;add AI capabilities such as AI-specific data management, synthetic data and data labeling &ndash; to your data management toolbox.&rdquo;
&ldquo;It&rsquo;s an honor to be named a Data-Centric AI Cool Vendor by Gartner. We believe that it is a testament to Scale&rsquo;s mission to accelerate the development of AI applications and showcases the market impact of our vision,&rdquo; said Alexandr Wang, CEO and Founder of Scale AI. &ldquo;The solutions that we provide enable organizations to reap the benefits of AI, whether they are building or applying AI. This means better business outcomes, a real return on investment, and a faster time to production.&rdquo;
According to the Gartner report, &ldquo;By 2025, 90% of new data and analytics deployments will be through an established data ecosystem, causing consolidation across the data and analytics market.&rdquo; Therefore, introducing a data management approach, such as data quality, data diversity, data and analytics governance, and data literacy to AI teams now, is imperative to any organization's AI strategy.
Download the full report <a href="https://www.gartner.com/doc/reprints?id=1-2C7YMC4Z&amp;ct=230109&amp;st=sb">HERE</a>.
Gartner Disclaimer
GARTNER and COOL VENDORS are the registered trademarks of Gartner Inc., and/or its affiliates and has been used herein with permission. All rights reserved. Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner&rsquo;s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.
About Scale AI
Scale accelerates AI development by providing the data infrastructure for AI. Its data-centric platform manages the entire ML lifecycle, from data annotation and curation to model testing and evaluation, enabling any organization &ndash; from the world&rsquo;s most advanced AI teams to legacy organizations &ndash; to develop and deploy impactful AI solutions. Scale combines ML technology with skilled human insight to ensure every AI application is built on a foundation of high-quality ground truth data. Scale is trusted by the largest technology companies in the world, including Microsoft, Toyota, Nuro, Samsung, Square, PayPal, SAP, Instacart, Pinterest, Brex, Flexport and U.S. government agencies like the U.S. Army and Air Force. Founded in 2016 and valued at $7.3 billion, Scale is backed by Founders Fund, Accel, Index, and Tiger Global.

Scale AI, the data infrastructure for AI, has been named a Cool Vendor in the 2022 Gartner Cool Vendors™ in Data-Centric AI.

Scale AI Named a 2022 Cool Vendor by Gartner® | Scale AI

Scale AI Named a 2022 Cool Vendor by Gartner®

Today, we&rsquo;re excited to announce the Early Access of Scale Forge (Beta) for AI-generated product imagery in seconds. With just a few clicks, marketers and brands can create stunning visual content for ad creatives, campaigns, and social media. Learn more and <a href="https://scale.com/catalog" target="_blank" rel="noopener noreferrer">sign-up for Early Access</a>.
<h2>Unlocking Stunning Product Imagery</h2>
Currently, retailers and advertisers are limited by the amount and quality of product photography they have to create an engaging shopping experience for customers. The investment needed for photoshoots, scale of product catalogs, and the diverse tastes of audiences adds to this burden. This limits the growth of businesses, and ultimately their ability to communicate their story and unique product offering to their audience.
Building on top of our existing strengths and technology in eCommerce, we built Forge to solve this problem.
<h2>Catalog Forge</h2>
With Forge, we&rsquo;re enabling customers to create AI-generated imagery via an easy-to-use design studio. Forge uses novel ML methods to allow for high-fidelity product and brand preservation for retail products.&nbsp;
With Forge, teams can:
<ol>
<li>Experiment and prototype quickly to decide the aesthetic of images</li>
<li>Operationalize and scale product image generation to enable servicing thousands of brands and products</li>
<li>Improve conversion with enhanced product images to maximize ROI&nbsp;&nbsp;</li>
</ol>
<a href="https://scaleai.wistia.com/medias/sk212njbxf" target="_blank" rel="noopener noreferrer">Video</a>
To get started, simply provide your product image, select a scene or describe your own, and create imagery through two ways:&nbsp;
<ol>
<li>Scene Enrichment: Create unique customizable scenes to generate product images that align with your brand values and product identity. Retain the original pose of each image. Best for: rigid objects</li>
<li>Full Transformation: Experiment with different poses, zoom levels, whole scenes, complementary products, and more. Only available for select demo products right now. Best for: clothing, fashion accessories</li>
</ol>
Forge enables you to create unique and memorable product images for your brand powered by AI.
<h2>New Era of Creativity in eCommerce and Retail&nbsp;</h2>
We&rsquo;re thrilled to introduce Scale Forge for eCommerce. We&rsquo;re excited to see what companies can create once they have access to the best quality AI tools. At Scale, we believe investing in data is the key to unlocking success for eCommerce companies, and we&rsquo;re just getting started.&nbsp;
To get Early Access for Forge, <a href="https://scale.com/catalog" target="_blank" rel="noopener noreferrer">sign-up for the waitlist</a>.

Catalog Forge is the fastest way to create AI-generated product imagery in seconds. Forge is now in Early Access.

Announcing Scale Forge: Available for Early Access 

Today we kicked off our third annual conference, TransformX, where the world's brightest AI leaders, visionaries, practitioners, and researchers engaged in conversations around the present and future of AI/ML.
At this year&rsquo;s event, we felt it was important to shine a light on how AI is going to define the next era of technology and power. Just like at the dawn of the internet, or cloud computing before it, the businesses that leverage AI will have an incredible competitive advantage to dominate their industries for years to come.&nbsp;
In fact, for many businesses, we&rsquo;re already at a nexus where it&rsquo;s AI or die. And that&rsquo;s because not all companies are equipped with the same resources to leverage the power of AI. Some organizations, often the biggest tech companies, are AI builders&mdash;they have the talent, resources, and experience to build their own, differentiated AI. But they often lack the high-quality data needed to feed their algorithms. On the other hand, there are organizations that aren&rsquo;t rooted in technology, but are prepared to leverage AI as a key asset and differentiator. They are looking to leverage this technology into their businesses without having to build their own ML team.
Whether an organization is already building AI or is at the starting line wanting to apply AI, it&rsquo;s clear that all organizations can reap tangible benefits from AI if they have the right tools and solutions tailored to their business. That&rsquo;s why today at TransformX, Scale introduced a suite of new products to unlock and operationalize AI for everyone &ndash; from startups to researchers and Fortune 500 companies to the U.S. government. These tools have already been battle tested in early access beta by companies such as <a href="https://opensea.io/" target="_blank" rel="noopener noreferrer">OpenSea</a>, <a href="https://www.voxelai.com/" target="_blank" rel="noopener noreferrer">Voxel</a> and <a href="https://picklerobot.com/" target="_blank" rel="noopener noreferrer">Pickle Robot</a>, and now they are fully available for everyone to adapt, develop and scale their use of AI.&nbsp;
<h2>Studio</h2>
Some labeling projects require in-depth subject-matter expertise. For example, medical initiatives have unique terminology and require deep domain knowledge. Studio provides organizations with the capability to run high quality, efficient labeling projects with their own team of experts. Features include the ability to pre-label datasets to reduce labeling time and auto-annotation to make it easy for anyone to label complex objects by simply drawing a box around the specific object. Studio supports all data types, including images, videos, audio, and text. Any team can quickly get started with Studio by signing up <a href="https://scale.com/studio" target="_blank" rel="noopener noreferrer">here</a>.&nbsp;
<h2>Nucleus Models&nbsp;</h2>
As many ML teams know, shipping a model isn&rsquo;t the end of the AI journey. To ensure a model performs well in all scenarios and avoids model failure in production, it is critical to test key scenarios beforehand. In 2020, we launched Nucleus, a new way to develop and test ML models. We are now improving Nucleus with new ML model testing functionalities that help catch regression over time and help teams to choose the best model through efficient model comparisons and scenario-level insights. Learn more about Nucleus and its model features <a href="https://scale.com/nucleus" target="_blank" rel="noopener noreferrer">here</a>.
<h2>Content Understanding AI</h2>
One of the biggest challenges for companies that invest in user-generated content is to recommend relevant content that keeps users engaged. With Content Understanding AI, product teams can easily enrich user-generated content to customize and iterate their content&rsquo;s taxonomy - ultimately increasing engagement. Data enrichment also gives product teams insights into their user&rsquo;s content, such as sentiment and mood, to help identify growth areas. Additionally, trend detection leverages ML techniques like clustering, topic aggregation and extraction, as well as Scale human-in-the-loop features to detect and understand new content trends surfacing on platforms. Learn more about Scale&rsquo;s Content Understanding <a href="https://scale.com/content-understanding" target="_blank" rel="noopener noreferrer">here</a>.&nbsp;
<h2>Document AI Go&nbsp;</h2>
In 2020, we launched Document AI to process complex documents up to near perfect accuracy in seconds. This year, we launched Document AI Go. Document AI Go is a self-serve machine learning platform that enables companies to quickly classify and extract data from their documents in just a matter of seconds. Unlike competing products, Document AI and Document AI Go are powered by foundation models and don&rsquo;t rely on templates, so they can handle the most complex and unstructured documents. Any organization can quickly sign up and start uploading documents <a href="https://scale.com/document-ai#pricing" target="_blank" rel="noopener noreferrer">here</a>.
We&rsquo;re thrilled to introduce these tools and put them in the hands of every company. We can only imagine what&rsquo;s possible when every company can access the best quality AI tools and tailored models. I believe that by making it easier for more companies to unlock and operationalize AI, we will experience a world where AI meaningfully supports humans as they solve the world&rsquo;s biggest problems.

At TransformX this year, we're sharing details on Studio, Nucleus Models, Content Understanding AI, and Document AI Go.