What is DeepSeek and why should you care? DeepSeek is an advanced AI language model designed to rival established tools like OpenAI’s ChatGPT and Anthropic’s Claude. Built with a focus on natural language processing (NLP), efficiency, and adaptability, DeepSeek is gaining attention for its potential to enhance AI-powered interactions in businesses, research, and everyday use. As AI becomes more deeply integrated into modern workflows, the emergence of new models like DeepSeek raises important considerations about performance, privacy, and security. Whether you’re a business looking for automation solutions, a developer exploring AI integrations, or an individual seeking smarter tools, understanding what DeepSeek offers can help you make informed decisions.

DeepSeek made headlines upon its launch, disrupting financial markets and raising eyebrows with its claimed development cost of just $6 million. This is a fraction of the reported billions spent by companies like OpenAI and Google DeepMind. If true, this would indicate a major shift in AI development costs, making powerful AI models more accessible to smaller companies and research institutions.

However, some experts have questioned whether DeepSeek’s reported cost is accurate, suggesting that the real investment behind its development may be significantly higher when accounting for computing resources, talent, and infrastructure. Regardless of the exact figure, the launch of DeepSeek signals a growing challenge to the dominance of AI giants, proving that new players can emerge with competitive models at potentially lower costs.

DeepSeek is gaining attention for several reasons. First, the AI landscape is changing rapidly, and businesses are looking for alternatives beyond OpenAI and Google, with many looking at moving away from US-based firms completely.

DeepSeek’s development suggests that companies want more choices in AI technology, particularly models that offer competitive performance with greater transparency and flexibility. Additionally, concerns over AI security and ethical use have sparked interest in models that prioritize responsible AI deployment. If DeepSeek introduces new safeguards for privacy and security, it could appeal to users who are wary of potential data risks associated with mainstream AI platforms.

What makes DeepSeek different from existing AI models lies in its potential architecture, scalability, and adaptability? While details about its framework are still emerging, it is expected to offer improvements in speed, contextual understanding, and customization options. Unlike proprietary AI models that restrict usage to specific platforms, DeepSeek may provide more open integration possibilities, allowing businesses and developers greater control over how they implement AI within their workflows. Another critical aspect is security—AI tools are increasingly scrutinized for how they handle user data, and if DeepSeek prioritizes data protection and ethical AI, it could set a new standard in the field.

We will take a look at DeepSeek in a little more detail, comparing its key features to other AI models, examining its potential use cases, and discussing critical security considerations. By the end, you’ll have a clear understanding of whether DeepSeek is an AI tool worth exploring and how it might fit into the future of AI-driven solutions.

DeepSeeks' Hero Page

Who Created DeepSeek and What Is Its Purpose?

DeepSeek was founded in 2023 by Liang Wenfeng , a former math prodigy and hedge fund manager. Based in Hangzhou, Zhejiang province, the company operates as a subsidiary of High-Flyer, a hedge fund co-founded by Liang.

Liang’s vision for DeepSeek was to develop advanced AI models that could rival those of leading Western companies, but at a fraction of the cost. This ambition was driven by a desire to democratize AI technology, making it more accessible and efficient. By leveraging innovative techniques and optimizing available resources, DeepSeek aimed to overcome the limitations imposed by international trade restrictions and the high costs typically associated with AI development.

From what we have seen in the media, DeepSeek’s primary objective is to create open-source large language models that deliver high performance without the need for extensive computational resources. This approach addresses several challenges in the AI industry, including the significant financial and environmental costs of training large models, and the barriers to entry for smaller organizations lacking substantial funding. By focusing on efficiency and accessibility, DeepSeek seeks to broaden the adoption of AI technologies across various sectors.

How Does DeepSeek Work?


DeepSeek is built using a cutting-edge technique called the Mixture of Experts (MoE), which makes it different from many other AI models like GPT-4 or Llama 3.  This means that instead of activating all parts of the model for every question or task, DeepSeek only uses the specific sections of its brain that are needed for the job. This helps it work faster and more efficiently while still providing highly accurate answers. In the simplest of forms, it’s like having a team of specialists, where only the right expert steps in to solve a problem.

DeepSeek V3, the latest version, uses 37 billion active parameters (like decision-making parts) out of a massive 671 billion total parameters, making it potentially one of the most advanced models out there. This design allows it to perform complex tasks without wasting unnecessary resources.

To train DeepSeek, its creators appear to have used a huge amount of data from different areas, such as language, coding, and math. This wide-ranging training helps it understand and respond to all kinds of queries. For example, in tests like DROP  (which measures how well it handles tricky reasoning questions), DeepSeek scored an impressive 91.6%, showing it’s highly capable at understanding and answering tough questions. This figure is sourced from the DeepSeek website, where it is compared to competitors in the market, such as GPT-4o, which scored 83.7%, and Claude-3.5, which scored 88.3%.

DeepSeek’s responses are generated by focusing on the specific task at hand. Whether it’s understanding language, solving a math problem, or writing code, it activates only the parts of its model trained for that area, making it fast and accurate. This ability to focus its “thinking” is meant to help it perform better and faster than many older AI systems.

By using smart technology and focusing on efficiency, DeepSeek has the potential to become a powerful tool for businesses, researchers, and individuals who need reliable and quick AI assistance across many fields. It’s designed to handle real-world challenges with precision and speed, making it a standout in the AI space.

deepseeks interface

DeepSeek vs ChatGPT

DeepSeek and ChatGPT are both AI-driven models designed for handling language-based tasks, but they are built with different priorities in mind. While ChatGPT is widely recognized for its conversational abilities, DeepSeek has been positioned as an alternative that focuses on structured responses and accuracy in technical fields.

Similarities

Both models generate text-based responses and can assist with a variety of tasks, from answering questions to drafting content. They are widely used in business, research, and creative fields, helping users streamline workflows and generate ideas.

Key Differences

  • Handling Complex Problems: As mentioned earlier, DeepSeek is reported to perform better in structured reasoning tasks, with a 91.6% score on the DROP benchmark. This suggests it may be stronger when responding to multi-step logic-based queries. ChatGPT, by comparison, may not always maintain accuracy in complex problem-solving.
  • Technical Focus: Some claim that DeepSeek is more reliable for coding, math, and structured data processing, making it better suited for tasks that require precision. ChatGPT, while still capable, sometimes provides responses that need further validation.
  • Processing Approach: Where DeepSeek uses a MoE model, activating only the necessary parts of its system for each request, this design reportedly allows it to generate more targeted answers.  ChatGPT applies a broader processing method that can lead to more general responses.
  • Reliability of Information: Some sources suggest that DeepSeek is less likely to generate misleading or incorrect information. ChatGPT, while capable of engaging discussions, occasionally presents confident but inaccurate responses, particularly in niche technical areas.

Where ChatGPT May Fall Short Compared to DeepSeek

Several reports highlight some of ChatGPT’s weaknesses in technical applications:

  • Factual Inaccuracies: According to Forbes, ChatGPT has been known to generate incorrect or misleading responses, sometimes filling in gaps with plausible but incorrect details.

DeepSeek may be more suitable for developers, researchers, and those working with structured data, as it is claimed to provide clearer and more reliable outputs in those areas. For professionals who rely on AI for more interpersonal work, brainstorming, and customer interactions, ChatGPT remains a strong choice due to its conversational abilities and broad knowledge base.

What Are the Key Features of DeepSeek?

DeepSeek has been positioned as a high-performance AI model designed to handle a wide range of tasks, but how does it actually perform in real-world applications? Below, we break down its key features to understand its strengths and potential limitations.

Natural Language Processing (NLP): Can It Handle Complex Queries?

DeepSeek is designed to process complex language tasks, including multi-step reasoning and structured data interpretation. As mentioned earlier, it has performed well on benchmarks like DROP, which test AI models’ ability to handle complex queries. While this suggests strong capabilities in structured reasoning, it remains to be seen how it performs in real-world conversational interactions compared to ChatGPT, which is widely regarded for its nuanced and natural dialogue.

Multimodal Capabilities: Can It Process Images, Audio, or Video?

Some AI models, such as GPT-4o, support multimodal input, allowing users to process images, audio, and even video. At present, DeepSeek appears to be primarily text-based, with no confirmed support for image or audio processing. If future versions expand into multimodal AI, this could significantly enhance its capabilities, but for now, it remains focused on text-based tasks.

Customization: Can Businesses Fine-Tune DeepSeek for Their Needs?

For AI adoption in business settings, customization is crucial. While OpenAI provides API access to GPT models, allowing some degree of fine-tuning, DeepSeek’s level of adaptability remains unclear. If it allows businesses to train and refine the model for specific tasks, this could make it a valuable alternative. However, without direct confirmation on fine-tuning options, it’s uncertain how much control users have over its outputs.

Speed & Response Time: How Fast Is It Compared to Competitors?

One of DeepSeek’s selling points is its MoE architecture, which selectively activates parts of the model rather than processing everything at once. This should, in theory, make it faster than fully dense models like ChatGPT. However, some users have reported server issues and slow response times, raising questions about its reliability in high-demand scenarios.

API & Integration: How Easy Is It to Connect with Other Tools?

APIs are critical for businesses looking to integrate AI into their workflows. While OpenAI and Anthropic provide well-documented APIs for their models, DeepSeek’s API availability and ease of use are still emerging topics. Developers will need to assess whether it provides the same level of accessibility and documentation as its competitors before considering it for large-scale applications.

Source: DeepSeek

What Is DeepSeek Used For?

DeepSeek is designed to handle a variety of tasks across different industries. Whether for business, research, creative projects, or everyday productivity, its capabilities are meant to be used in a number of ways:

Business Applications: Customer Support, Automation, Content Generation

DeepSeek has the potential to be integrated into customer service platforms, helping businesses manage inquiries efficiently. While models like ChatGPT are widely used in chatbot services, DeepSeek’s structured approach could be beneficial for handling precise, technical, or data-driven responses.

Automation is another area where AI models play a crucial role. Businesses can hypothetically use DeepSeek to assist with report generation, financial analysis, or workflow automation, reducing manual effort and improving efficiency. Additionally, content teams could explore DeepSeek for product descriptions, and marketing material, though its effectiveness in creative applications compared to more conversational AI models remains to be seen.

Academic & Research Uses: Data Analysis, Summarization, Language Translation

DeepSeek’s reported strengths in structured reasoning suggest it could be useful for academic research and data analysis. Researchers can use AI to summarize large volumes of information, extract key insights, and assist with literature reviews.

In education, DeepSeek could support language translation for multilingual content, aiding students and professionals who need high-quality translations. If its language processing capabilities match or exceed existing models, it may become a useful tool in academic settings for tasks like summarizing research papers or generating study materials.

Creative Uses: Writing, Coding, Brainstorming Ideas

Creative professionals use AI to enhance productivity, whether for drafting content, brainstorming, or writing code. DeepSeek’s structured processing may make it particularly useful for coding tasks, helping developers debug issues, generate scripts, or optimize algorithms.

For writers, AI can assist in generating outlines, refining content, or exploring alternative phrasing. However, given DeepSeek’s reported technical focus, its suitability for creative writing and storytelling compared to more conversational models like ChatGPT remains uncertain.

Everyday Productivity: Note-Taking, Scheduling, Quick Answers

AI tools are increasingly being used for personal productivity, helping users manage tasks, take notes, and stay organized. DeepSeek could be integrated into digital assistants for quick information retrieval, summarization, or scheduling support.

For individuals who rely on AI to boost efficiency, DeepSeek may offer an alternative for structuring and analyzing information. If its response speed and reliability improve, it could be positioned as a useful tool for everyday tasks, complementing or competing with existing AI-powered productivity tools.

Initial Reactions To DeepSeek

The launch of DeepSeek has ignited lively discussions across professional networks and social platforms. On one side, there is a wave of excitement, with many hailing it as a long-awaited challenger to established AI leaders like OpenAI and Google. Industry professionals have highlighted its affordability, with claims of a $6 million development cost sparking both intrigue and skepticism. Others are impressed by its technical benchmarks, suggesting it could be a game-changer for structured reasoning and efficiency in AI applications.

However, concerns have emerged about its origins and potential geopolitical implications. The fact that DeepSeek is backed by a Chinese hedge fund has prompted discussions around data governance, privacy, and regulatory compliance. This is particularly for businesses operating in the U.S. and Europe. Some worry that these factors could complicate its adoption, even as it garners interest for its innovative architecture and open-source accessibility.

DeepSeek’s debut has divided opinion. While many view it as a symbol of progress and competition in the AI space, others urge caution, emphasizing the need for thorough testing and transparency before it can be fully embraced as a viable alternative to established AI models.

How Safe Is DeepSeek to Use?

AI tools are powerful but require careful security measures to prevent data misuse. Whether using ChatGPT, Claude, or DeepSeek, businesses should assess where their data is stored, how it’s processed, and whether it meets compliance standards. DeepSeek, like other AI models, collects and processes user inputs, but its data policies and geographic ties bring additional considerations. While it offers advanced capabilities, it’s important to assess whether it aligns with your security requirements.

How Does DeepSeek Handle User Data?

DeepSeek, according to its privacy policy, collects user interactions, including text inputs, uploaded files, and feedback. Like many AI models, this data is used to improve the system. However, one key difference is that DeepSeek’s servers are reportedly located in China, which may impact data access and governance.

Key Considerations for Security and Privacy

  • Where is data stored? DeepSeek’s storage location matters because data privacy laws vary by country. Businesses operating in regions with strict data compliance requirements should consider where their information is processed and held.
  • Who has access to the data? While DeepSeek states that it follows security best practices, Chinese data laws allow government authorities to request access to information stored within the country. This may raise concerns for companies handling confidential or regulated data.
  • How long is data retained? The platform does not publicly disclose specific retention policies, which means users don’t have clear insight into how long their data is stored or when it is deleted.
  • Does DeepSeek store interactions? AI models often retain some interactions to refine their responses, but the extent of DeepSeek’s data storage remains unclear compared to more widely documented AI platforms like OpenAI’s ChatGPT.
  • Does it censor certain topics? Reports from media outlets, including The Guardian, indicate that DeepSeek has been observed censoring responses related to politically sensitive topics. While content moderation exists in all AI models, users should be aware that DeepSeek may provide restricted answers depending on the subject.
  • What does this mean for international businesses? For companies operating in regions with complex international relations, the geopolitical aspect of AI usage is worth considering. Some organizations may face compliance or security challenges if AI tools are subject to external oversight. TechRadar highlights that even OpenAI CEO Sam Altman has acknowledged DeepSeek’s advancements but suggests future AI competition may be influenced by broader security concerns.

For users in certain industries, such as finance, legal, or healthcare, carefully reviewing DeepSeek’s data policies before adoption is advisable. Being aware of where and how AI processes information helps businesses make informed choices that align with their security and compliance needs.

What Is Janus and Janus-Pro-7B?

On January 27, 2025, DeepSeek announced the release of Janus-Pro-7B , an advanced open-source AI model designed for text-to-image generation. According to DeepSeek’s press communications, Janus-Pro outperforms other leading models like OpenAI’s DALL-E 3 and Stability AI’s Stable Diffusion in benchmark tests.

The launch of Janus-Pro follows DeepSeek’s earlier release of R1, an AI model designed for logical inference and problem-solving. Together, these developments signal DeepSeek’s ambition to compete directly with industry leaders across multiple AI disciplines, from language models to visual generation and reasoning-based AI.

While early reports highlight Janus-Pro’s potential, further independent testing will determine whether it delivers on its claims. The release has already sparked interest in the AI community as DeepSeek continues to expand its technology stack beyond large language models.

We also asked DeepSeek itself about the launch of Janus. However, where DeepSeek is not a live model, the information within DeepSeek itself only goes up to October 2023. This may change later on, but it is definitely something to consider if looking to test and try it. 

DeepSeek's response when asked about its latest development
Source: DeepSeek

What Is tl;dv Doing to Ensure AI Security?

tl;dv is committed to ensuring the security and privacy of user data, especially when integrating AI technologies into its platform. Here’s an overview of the measures tl;dv has implemented:

Data Encryption and Compliance

tl;dv employs encryption protocols to protect meeting recordings and transcripts both during transmission and while stored. This approach ensures that data remains confidential and secure from unauthorized access. Additionally, tl;dv adheres to GDPR regulations, underscoring its dedication to data protection and user privacy.

Integration with Anthropic’s Claude

In partnership with Anthropic, tl;dv has integrated Claude, an AI system designed with a focus on safety and privacy. Notably, tl;dv ensures that no customer data is used to train the AI. Mechanisms have been added to keep user data safe and secure during AI processing.

Data Anonymization and Access Control

To further protect user privacy, tl;dv anonymizes data shared with Anthropic. Personal identifiers such as email addresses, company names, and user names are removed before processing. Additionally, access to meeting recordings and transcripts is restricted to authorized personnel only, ensuring that sensitive information remains confidential.

Why tl;dv Chose Claude Over Other AI Models

While some AI models have less transparent security policies, tl;dv integrates Claude, developed by Anthropic, because of its strong privacy safeguards and ethical AI framework. This ensures that user data is handled with security and compliance in mind, offering businesses a more privacy-conscious AI solution.

How to use DeepSeek – How To Get Started. And Should You?

DeepSeek is available for users to explore, but how you access it depends on its current release stage and whether you need it for personal or business use.

How to Access DeepSeek

DeepSeek offers free access through its website and mobile apps, allowing users to sign up using a Google account. Currently, there is no confirmation on a premium or enterprise-tier model, but as the AI market evolves, it’s likely that more structured pricing or service levels will emerge. Developers can also interact with DeepSeek’s open-source API, which follows OpenAI’s API format, making integration easier for those already working with AI tools.

How to Integrate DeepSeek Into Workflows

For developers and businesses, DeepSeek provides an API key through the DeepSeek Open Platform, allowing companies to integrate its capabilities into their applications. Resources, including documentation and community discussions, are available on DeepSeek’s GitHub, where users can find guides for setting up the model.

Considerations Before Using DeepSeek

While DeepSeek presents itself as a competitive AI model, users should be aware of data privacy concerns. As mentioned earlier, DeepSeek’s data storage policies and the location of its servers may impact regulatory compliance, particularly for businesses operating in the U.S. and Europe.

Unlike AI companies based in the U.S. or EU, where data privacy laws like GDPR set clear guidelines, companies using DeepSeek should carefully review how it handles user information. While this is a consideration with any AI model, different regions have different expectations, and businesses should evaluate the risks before integrating DeepSeek into sensitive workflows.

How good is DeepSeek? Is It Worth It?

Maybe in the future, but not quite yet. There are a lot of claims, a lot of concerns, and while many of these could be completely unfounded, there’s still a level of uncertainty that extends beyond just the technology itself.

To recap it all, DeepSeek is an emerging AI model that has generated interest for its efficiency, structured reasoning, and potential lower cost of development compared to competitors like ChatGPT and Claude. It stands out for its Mixture of Experts architecture, which selectively activates different parts of the model for better performance in technical and structured tasks such as coding, data analysis, and problem-solving. However, it remains untested in broader real-world applications, particularly in conversational AI, creativity, and business integration.

For developers and researchers, DeepSeek may offer a useful alternative for handling complex reasoning and structured data tasks. Businesses looking for AI solutions beyond OpenAI and Google could explore its capabilities, but considerations around security, data privacy, and regulatory differences should be factored into the decision. While DeepSeek has the potential to challenge established AI leaders, its long-term impact and reliability remain to be seen.

The one thing we are certain of? tl;dv’s commitment to security and privacy is clear.