Deepseek vs ChatGPT

DeepSeek has taken the Generative AI world by storm! And it is threatening to take the central spot that ChatGPT carved for itself. So, let’s take a look at both tools, from a user perspective.

One of the most notable distinctions is accessibility; DeepSeek is currently available for free, while ChatGPT operates on a freemium model - DeepSeek's free availability may make it more accessible to a wider range of users compared to ChatGPT's tiered pricing structure.

In terms of performance, DeepSeek reports that it excels in speed for complex tasks (math, physics, reasoning,…) and demonstrates strong capabilities in coding. ChatGPT, from its side, offers proved multimodal functionalities, processing and generating text, images and audio, and integrates various tools (like web browsing and data analysis tools) that enhance user experience.

Language support is another area where these two platforms differ. DeepSeek primarily supports English and Chinese, while ChatGPT boasts broader language coverage, making it more versatile for a diverse user base – it is actually quite good at Portuguese, let me tell you. Additionally, both platforms provide integrated search features, but many users find ChatGPT's interface to be more user-friendly and organized.

Another significant difference lies in their underlying structures: DeepSeek is based on an open-source model, which could provide potential customization and integration options for developers, while ChatGPT is a proprietary service. Having said this, ChatGPT’s ability to create specific solutions for a non-developer user (as myself) never has never let me down.

However, it's crucial to consider some caveats regarding DeepSeek. The platform has raised concerns about data privacy since user data is stored in China and may be subject to local regulations requiring data sharing with authorities. Additionally, DeepSeek has been found to be more vulnerable to jailbreaks which can bypass safety mechanisms and potentially generate harmful or inappropriate content. Furthermore, DeepSeek exhibits self-censorship on sensitive topics, particularly those related to China, which could lead to biased or incomplete information. These factors may limit its reliability for users who require unbiased insights or have heightened privacy concerns. Lastly, while DeepSeek performs well in certain areas, like coding and reasoning tasks, it can still produce inaccuracies or hallucinations like any other generative AI model

Users should weigh these considerations carefully when deciding between the two platforms. What has been your experience with these AI chatbots? I'd love to hear your thoughts!

Maybe we need to have a serious conversation

Over the past few months, OpenAI announced both Sora and Operator - none of them available in the EU. If you think AI’s over regulation won’t affect productivity… well… think again…

The top three concerns of Portuguese marketers

"Artificial Intelligence", "Brands" and "Sustainability" are the top three concerns of Portuguese marketers, according to the latest study from APPM - Associação Portuguesa dos Profissionais de Marketing . And I would say it is not by chance!

The fusion of AI and Sustainability isn't just a trend; it's a necessity for future-proofing businesses. By leveraging AI, we're not only optimizing operations but also finding innovative ways to promote sustainability and customer experience. This dual focus reflects our commitment to both technological advancement and environmental stewardship - and, together, with strong customer-meaningful brands, will be key for navigating a very dynamic future!

The next 10 years will be exciting! And it will be for all of us if we decide to proactively create the right opportunities on this evolving landscape, or if we sit on the side and passively let be engulfed by change.

A reminder of the heavy costs of Climate Change

As the financial toll of the LA urban wildfires amounts to over $100Bs (and the personal losses of them can't really be calculated), we are reminded of the heavy costs that climate change will impose on all of us.

I am quite sure that impacted businesses and insurance companies are now doing their maths, and understanding how can they mitigate their risks on urban wildfires in the future - and this is, by the way, a global risk, not confined to Southern California. One should expect insurance costs to rise for people and businesses, to account for the increased risk - and better urban planning and the smart usage of fire-resistant trees to be demanded to mitigate risks and costs.

https://www.linkedin.com/feed/update/urn:li:activity:7286719784275111937/

About waste

In 1995, Michael Porter (yes, that Michael Porter) wrote that “every consumption of resources made by a company, if it doesn't go into the final product that is sold on the market, is a loss of efficiency”. And to be honest, that’s really hard to argue against – because one is spending money on a resource that will not add value to the customer. And that’s why one designs for purpose – you should develop your products to maximize the impact (aka value added) to your customer (but not a “nail” beyond it).

Now, there is another really cool dimension about this sentence from Porter. If you look at it with your sustainability lenses on, you find that he could be advocating for circular economy. Because, if I am a company, and I want to take the best out of the circular economy, what I have to do is to try to save resources, or to recover, reuse, recycle the materials that otherwise are going to be lost. If it doesn't go to the final consumer, it doesn't get any value from the market, and is just waste.

In the end, it all starts with design – 80% of a product’s environmental impact is locked there. But also the most of the value one will add to the customer. And it is not a matter of balancing these two things – it is a matter of aligning them.

P.S.- Want an example, look at the great Skip Quick Wash launch all over Europe.

Business differentiators

A few years of experience in tech environments and I can tell you one thing: I am really convinced that technology is enhancing the importance of human skills as business differentiators.

Most people think of decisions as right or wrong, 1 or 0, all or nothing. But decision is more complex - right or wrong are probably not the best way to look at them.

Decision making is about managing a range of outcomes. Of balancing or hedging outcomes within a range of probabilities. That’s essentially for two reasons:
- no decision should be looked at in isolation. There is usually no single “press of a button”. There are many decisions that are taken on a project (or strategy) that should be looked at as a system - and that gives you variables that you can play with to manage desired outcomes and risk.
- And then there is implementation. And implementation of the decision is key for success, for the desired outcome. I have seen (probably) bad decisions that produced great results, because the whole team (including the decision maker) performed brilliantly and made it work.

So, my stance is that decisions should always be looked at systemically, their outcomes as a range and implementation as key for success of any strategy or project.

P.s - And “timing” is a whole new book…