23 January 2025

DeepSeek R1: The FREE AI That's Beating OpenAI’s o1 Model

1Frameworks

7Insights

Frameworks in this episode

Marketing6 steps

Internal-External Campaign Analysis Loop

Turn campaign data and market trends into an evidence-based action calendar.

Read →

Insights & moments

The myth-busts, hot takes, explainers, and tools worth keeping.

Hot Take· 3

Hot Take02:30

The Cost of Machine Intelligence Is Heading Toward Pennies

The host highlights the dramatic price difference between DeepSeek R1 and OpenAI's o1, then draws out the broader implication. If reasoning capability continues becoming cheaper, advanced intelligence could become widely accessible rather than remaining a scarce premium resource.

DeepSeek R1 is described as substantially cheaper than o1.
Open-source capability may trail leading closed models by only months.
Falling token costs broaden access to advanced reasoning.
Cheap intelligence could have civilization-scale consequences.

“DeepSeek R1, is 100% open source. It's 96.4% cheaper than OpenAI's o1 models, right?”
02:30

“we're going to get to a point in civilization where intelligence and reasoning that is above what a human can do is nearly given away…”
03:30

#ai-costs#intelligence#access#economics

Hot Take06:00

No Single AI Model Will Be Best at Every Task

The host distinguishes reasoning-oriented models from models that feel stronger at creative work, singling out Claude for writing and creative interaction. The larger point is that model selection should depend on the job rather than brand loyalty or a universal leaderboard.

Reasoning models are strong at mathematics, coding, and science.
Claude is presented as particularly strong for creative tasks.
Interaction style can matter alongside benchmark performance.
Organizations benefit from preserving access to multiple models.

“They are really good at logical and reasoning kind of problems like maths, coding, science”
06:00

“Claude is like much better for creative tasks.”
06:30

#model-selection#claude#deepseek#ai-workflows

Hot Take12:00

Open-Source Reasoning Models Will Accelerate AI Evolution

The closing prediction is that releasing capable models openly will speed up fine-tuning, experimentation, and derivative development. The host expects rapid model evolution as more builders gain access to strong foundations.

Open releases let more developers build on frontier-like capability.
Fine-tuning can happen rapidly across many use cases.
Benchmark competition is expanding beyond established labs.
The pace of model improvement is expected to accelerate.

“These models being open sourced is just going to mean that people are going to start to fine tune these things and build upon them…”
12:00

“This year we are going to see an incredible speed pace evolution of models.”
12:30

#ai-forecast#open-source-ai#innovation#deepseek

Explainer· 3

Explainer00:30

Why DeepSeek R1 Challenges the Closed-Model Leaders

DeepSeek R1 is presented as an open-source reasoning model with released papers, weights, and implementation information. The episode argues that its performance makes it a significant challenge to companies attempting to differentiate primarily through proprietary models.

The model is free to use and build upon.
Its papers and model weights were released publicly.
The host compares its reasoning ability with OpenAI's o1.
The launch puts competitive pressure on closed-model providers.

“They have open sourced the model. It's free to use.”
00:30

“it's comparable in terms of power to ChatGPT and OpenAI's o1.”
01:00

#deepseek#open-source-ai#reasoning-models#competition

Explainer05:30

Open Models Create a Market for Audience-Specific AI

The episode argues that a powerful open foundation model can be fine-tuned for specialized tasks and audiences. This could enable businesses to develop narrowly differentiated AI products without creating a frontier model from scratch.

Open foundation models lower the barrier to customization.
Fine-tuning can target a specific creative or commercial task.
Audience specialization can become a product differentiator.
Released technical papers help builders understand the underlying model.

“you can really start to build your own models, because you have the foundational model, like a DeepSeek, which is comparable to o1 for free”
06:00

“there's going to be a large market for actually taking these markets and building these different types of models that are very specific for a…”
07:00

#fine-tuning#open-source-ai#vertical-ai#product-development

Explainer07:30

The Enterprise AI Stack Will Route Tasks Across Models

Rather than committing to one provider, the host predicts that businesses will combine specialized open and closed models. An orchestration layer would evaluate each task and call the model best suited to perform it.

Vendor lock-in is undesirable when model strengths differ.
Open models can be fine-tuned for internal tasks.
Closed models can remain available where they perform better.
An orchestration layer can route work dynamically.

“I don't think companies want to be tied into a singular model”
07:30

“have a layer, an orchestration layer, that will call the different models when they need it.”
07:30

#orchestration#enterprise-ai#multi-model#vendor-lock-in

Takeaway· 1

Takeaway04:00

Read the Model's Reasoning to Learn How It Approaches Problems

DeepSeek's visible reasoning process is described as unusually natural and useful to inspect. Beyond obtaining an answer, users can study how the model decomposes a problem, considers alternatives, and organizes its search for a solution.

The model exposes a visible reasoning process.
Its internal monologue feels comparatively natural.
Reading the process can reveal useful problem-solving approaches.
Web access and citations support research-oriented questions.

“It's doing like an internal monolog, thinking to itself, reasoning to itself, thinking through the problem.”
04:00

“to see how an AI model is actually approaching any problem you may have.”
04:30

#reasoning#problem-solving#ai-literacy#deepseek