DeepSeek vs OpenApi

1 . Efficiency –

DeepSeek activates only needed parts of the model,

while OpenAI fully activates everything, making DeepSeek more resource-efficient.:

2 . Efficient Architecture:

DeepSeek uses a "mixture of experts" technique, which activates only necessary computing resources, making it more efficient than OpenAI's traditional approach.

3 . Open-Source Advantage:

Unlike OpenAI’s proprietary models, DeepSeek has open-sourced its model, allowing developers worldwide to access and build on it.

Openness – DeepSeek is open-source and transparent, while OpenAI is closed and a black box, giving DeepSeek an edge in community contributions.

4 . Cost :

DeepSeek is 95% cheaper than OpenAI regarding training costs and is 20–40 times cheaper per token.

DeepSeek trained its model (DeepSeek-R1) for just $5.6 million,

whereas OpenAI's models cost between $100 million and $1 billion

In short, DeepSeek is cheaper, more efficient, open-source, and resource-friendly,

while OpenAI is more costly, closed, and cloud-dependent

5 . Comparison of Reinforcement Learning Approaches:

OpenAI
Method: RLHF (Reinforcement Learning with Human Feedback)
Cost: Very High
Details: It requires human annotators which may increase costs and require complex infrastructure.
DeepSeek
Method: GRPO (Rule-Based Rewards)
Cost: Low
Details: This method uses automated rules, eliminating the need for human involvement, and making it more efficient and less costly.

Founded

2023 by Liang Wenfeng

2015 by Elon Musk, Sam Altman, et al.

Mission

Open-source AI for accessibility

Ensure AGI benefits all of humanity

Key Model

DeepSeek-R1

GPT-4

Development Cost

< $6 million

Hundreds of millions of dollars

Approach

Fully open-source

Proprietary

Performance (Math)

79.8% on AIME benchmark

79.2% on AIME benchmark

Performance (General)

Specialized (math, coding)

Versatile, excels in multiple domains

Speed

Record-breaking inference speeds

High-speed but resource-intensive

Use Cases

Problem-solving, coding, mathematical tasks

Creative writing, translation, general NLP

Access

Free and open to everyone

Paid APIs and commercial partnerships

Market Impact

Disrupted AI norms with cost-effective models

Industry leader with partnerships (Microsoft)

Ethics/Safety

Promotes transparency, shared responsibility

Focused on controlled, safe AI deployment

Target Audience

Developers, startups, researchers

Enterprises, large-scale businesses

Notable Collaboration

Open-source community

Microsoft, Azure

Innovation

Cost-effective AI at scale

Pioneering large-scale proprietary models

🚨 DeepSeek AI's Exposed Database: A Security Blunder We Can't Ignore!

Wiz researchers recently discovered that a misconfigured DeepSeek AI database exposed AI model data at risk to would-be attackers

What Went Wrong?

🔎 Wiz’s security team uncovered an exposed DeepSeek AI database with zero authentication or access controls in place.
🌍 It was freely accessible to anyone on the internet—no restrictions, no security barriers.
Misconfiguration could lead to data theft, model poisoning, or unauthorized access.

How Do We Prevent Security Failures Like These?

1 . Secure by Default – Always enforce authentication & access controls before going live. 🔒
2. Least Privilege Access – Restrict access to only those who truly need it. 👨‍💻🔑
3. Continuous Monitoring – Detect and fix misconfigurations before attackers do. 🛡️
4. Shift-Left Security – Integrate security early in the DevOps pipeline. 🚀
5. Automated Audits – Regularly scan, review, and patch cloud security vulnerabilities. ⚙️✅

⚠️ And Why This Should Worry You

🚨 One misconfiguration can expose entire systems to cyber threats.
🧠 AI-driven platforms like DeepSeek AI handle highly sensitive, proprietary data, making them a prime target for attackers.
🔓 Never have security be an afterthought. It should be paramount!

💡 Security is not a feature, but a necessity! 🔥

🔎 What security measures do you use for your infrastructure?
Drop your thoughts in the comments! 👇💬