Founded in 2017, Stardust AI is dedicated to unlocking the full value of data, making AI accessible, and empowering businesses to gain a competitive edge with high-quality data in the AI 2.0 era. Serving and collaborating with businesses across various industries worldwide, Stardust AI partners with renowned international enterprises such as SAIC MOTOR Group, BYD, Geely, Bosch, ZF, Xiaomi, and JD.com.

Meridian Capital Asia is proud to have led Stardust AI’s Series A financing round in 2022. Stardust AI’s strength lies in the comprehensive AI lifecycle data full-stack system, constantly pussing the envelope in data creation, management, corner cases data mining, and model analysis. The rise of large language models (LLMs) has spurred the demand for the engineering processing of massive amounts of unstructured data, which is precisely Stardust AI’s core advantage. Together with its global partners, we believe Stardust AI is committed to offering smoother, more accessible, and state-of-the-art data services to the AI industry.

On the evening of July 7, the 2024 World Artificial Intelligence Conference (WAIC) concluded successfully in Shanghai. As an annual industry extravaganza, WAIC brought together top enterprises, industry leaders, and innovative companies from around the globe to discuss the latest advancements and future trends in AI. Stardust AI was honored to participate as an exhibitor throughout this year’s conference.

(Figure 1: Visitors are surrounding Stardust AI’s booth)

The presence of Stardust AI at the event aimed to showcase the latest enhancements to MorningStar since its 2024 launch, including the unveiling of the MorningStar SaaS beta and the “Navigator” plan.

MorningStar is an AI-powered data engine designed to enable businesses to fully leverage the value of their internal data. It facilitates the integration of multimodal unstructured data such as images, videos, point clouds, audio, and text. Using a visual data flow approach, it manages the entire lifecycle of AI data, enabling functions like data synthesis, human feedback, and corner case detection.

CEO and Co-founder Derek’s presentations on July 5 and 6 were warmly received, sparking lively discussions and underscoring the public’s strong interest in AI advancements.

(Figure 2: Stardust AI’s CEO & Co-founder Derek interacts with the young audience after the presentation)

In his presentation, Derek not only shared the latest research achievements of Stardust AI but also inspired the audience’s boundless imagination about the future applications of artificial intelligence. In the era of AI 2.0, having control over one’s data means having control over one’s models.

From the Past to the Present: How Enterprises Harness Their Data Effectively

In this data-driven era, corporate decision-making increasingly relies on the rich internal data resources accumulated over time. Traditionally, businesses have focused on leveraging structured data, such as statistical insights derived from big data analytics, to guide strategic planning and day-to-day operations. However, this appraoch may only scratch the surface of the potential of corporate data. In fact, structured data represent only a small fraction—approximately 20%—of all valuable information within an enterprise.

Enterprises also harbor an underutilized treasure trove within their ranks: unstructured data. This encompasses a variety of formats, including PDF files, text documents, images, chat logs, videos, and audio recordings, which account for the remaining 80% of valuable information. Despite the immense potential value of these unstructured data, they are often overlooked due to the absence of effective analytical tools and methodologies.

(Figure 3: There are vast amounts of unstructured data within a corporation, ready to be fully utilized through LLM Agent)

With the progression of AI and machine learning, companies are poised at a pivotal moment to unleash the power of unstructured data through advanced analytics. This advancement promises to deepen insights and bolster decision-making, thereby sharpening competitive advantage and fueling industry innovation.

Post the introduction of large language models (LLMs), training AI with extensive datasets has become feasible. By fusing these models with a complete data spectrum, businesses can maximize the value of their internal data, offering a new depth and breadth in decision-making.

Charting the Future: AI Data’s Evolution and Growth Trajectory

In the foreseeable future, the data resources required for AI model training are undergoing a profound transformation. Since the rise of large datasets like ImageNet, there has been a quest for even larger datasets, but it appears that AI models have now tapped into nearly all the available data on the internet.

Faced with the potential depletion of human and natural world data, how will the future learning path of AI unfold? This is a question that merits deep contemplation.

The impending era of AI will hinge on three pivotal data needs:

1. a) Supervised Learning Data: Essential for AI, future advancements in auto-labeling will streamline the labeling process, prioritizing both efficiency and precision.
2. b) Synthetic Data: As few-shot learning evolves, synthetic datasets generated algorithmically will augment AI training, broadening the learning scope despite a constrained pool of real-world data.
3. c) Human Interaction Data: Currently rare, these datasets capture the intricacies of human actions and decisions. With the integration of Augmented Reality (AR) and Virtual Reality (VR) technologies, they are poised to become a cornerstone for enriching AI’s learning resources.

(Figure 4: MorningStar’s Advanced Algorithm Identifies Corner Case in Autonomous Driving)

Data tools on the market must evolve to address the multifaceted needs of AI data. Innovation in data collection, processing, and analysis, coupled with more intelligent data generation techniques, is imperative for the future trajectory of AI. This challenge is also a gateway to significant progress in the AI domain.

MorningStar: The AI-Powered Data Engine Unlocking the Full Value of Corporate Data

MorningStar is revolutionizing the field of AI data tools with its unique approach, helping enterprises fully exploit their internal data resources. By accelerating the iteration process of corporate AI models and facilitating the swift deployment of AI applications, MorningStar is unlocking the full value of corporate data and driving the next wave of AI innovation.

(Figure 5: The ideal users for MorningStar)

MorningStar delivers substantial value across three key areas:

1. a) Data Production: MorningStar equips businesses with efficient and accurate data production capabilities through automated data annotation, data synthesis, and human feedback mechanisms. These features enhance data usability and lay a solid foundation for AI model training.
2. b) Data Insights: Offering tools for process management, statistics, metric tracking, and data security, MorningStar helps businesses uncover patterns and trends behind the data to inform strategic decisions.
3. c) Data Intelligence: At the pinnacle, MorningStar integrates full-spectrum data application and exploration, supports business operations with intelligent agents, and elevates operational efficiency and decision quality.

With these solutions, MorningStar supports businesses from raw data to intelligent applications, propelling their transformation in the AI 2.0 era, therefore, establishing itself as a formidable data engine for the times.

MorningStar SaaS Version now open for Free Trial Access

(Figure 6: Scan to Register for a Free Trial of MorningStar SaaS Version)

Exploring the Data Ocean, Steering Future Research — Welcome to Stardust AI “Navigator” Plan

Stardust AI proudly announces the launch of the “Navigator” plan, offering free access to MorningStar for researchers and young scholars to advance academic research and technological innovation.

In today’s information-rich environment, these scholars are the vanguard of discovery and innovation. Recognizing their boundless potential, the “Navigator” plan provides a new research platform for the next generation of AI academic leaders. The MorningStar Educational Edition, designed for the intricate demands of AI data research, is now available free to scholars worldwide to explore this innovative tool.

Join the “Navigator” program and you will receive:

1. a) Exclusive access: Unlimited use of the MorningStar Educational Edition throughout the program duration.
2. b) Dedicated support: Timely technical assistance from the professional team to ensure seamless research progress.
3. c) Early access to new features: As a Navigator, you’ll have the opportunity to experience the latest product features before anyone else, and even contribute to the product’s development.
4. d) Academic exchange platform: Engage with our Navigator community to exchange ideas with scholars worldwide and drive progress in the AI academic field.
5. e) Opportunity to showcase achievements: Your research outcomes could be featured on domestic and international platforms for broader recognition and attention.

Scan the QR code in Figure 6 to join the “Navigator” program and start your innovative journey!