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How can you make use of DeepSeek R1 for ?

Serhii Melnyk

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I constantly desired to collect statistics about my performance on the computer. This idea is not brand-new; there are plenty of apps developed to fix this problem. However, accc.rcec.sinica.edu.tw all of them have one considerable caveat: you need to send highly sensitive and individual details about ALL your activity to "BIG BROTHER" and trust that your data won't end up in the hands of personal information reselling companies. That's why I chose to create one myself and make it 100% open-source for total openness and dependability - and you can use it too!

Understanding your performance focus over an extended period of time is necessary because it offers valuable insights into how you designate your time, determine patterns in your workflow, and find locations for improvement. Long-term performance tracking can help you pinpoint activities that regularly add to your objectives and those that drain your energy and time without significant outcomes.

For instance, tracking your efficiency trends can expose whether you're more effective during certain times of the day or in particular environments. It can also help you evaluate the long-term impact of changes, like altering your schedule, adopting brand-new tools, or taking on procrastination. This data-driven technique not only empowers you to enhance your daily regimens however also assists you set sensible, attainable goals based upon proof instead of assumptions. In essence, comprehending your efficiency focus over time is a vital action toward producing a sustainable, effective work-life balance - something Personal-Productivity-Assistant is created to support.

Here are main features:

- Privacy & Security: No details about your activity is sent out online, ensuring complete personal privacy.
- Raw Time Log: The application stores a raw log of your activity in an open format within a designated folder, providing full openness and user control.
- AI Analysis: An AI model evaluates your long-lasting activity to uncover hidden patterns and provide actionable insights to enhance productivity.
- Classification Customization: Users can by hand change AI classifications to better show their individual efficiency goals.
- AI Customization: Today the application is utilizing deepseek-r1:14 b. In the future, users will be able to select from a range of AI models to fit their particular requirements.
- Browsers Domain Tracking: The application likewise tracks the time spent on specific websites within web browsers (Chrome, Safari, Edge), providing a detailed view of online activity.
But before I continue explaining how to have fun with it, let me state a couple of words about the main killer feature here: DeepSeek R1.

DeepSeek, a Chinese AI startup founded in 2023, has actually just recently gathered substantial attention with the release of its latest AI model, R1. This model is notable for its high efficiency and cost-effectiveness, placing it as a powerful rival to established AI designs like OpenAI's ChatGPT.

The model is open-source and can be operated on computers without the need for substantial computational resources. This democratization of AI innovation permits people to explore and assess the model's abilities firsthand

DeepSeek R1 is bad for whatever, there are sensible concerns, however it's best for our productivity tasks!

Using this design we can classify applications or websites without sending any information to the cloud and thus keep your information protect.

I strongly believe that Personal-Productivity-Assistant might cause increased competitors and drive development across the sector of comparable productivity-tracking services (the integrated user base of all time-tracking applications reaches tens of millions). Its open-source nature and totally free availability make it an exceptional option.

The design itself will be provided to your computer system by means of another task called Ollama. This is done for benefit and better resources allotment.

Ollama is an open-source platform that enables you to run big language designs (LLMs) in your area on your computer, boosting data privacy and control. It's compatible with macOS, Windows, and Linux running systems.

By running LLMs locally, Ollama makes sure that all information processing happens within your own environment, getting rid of the need to send delicate details to external servers.

As an open-source project, Ollama gain from constant contributions from a lively community, making sure routine updates, function enhancements, and robust assistance.

Now how to set up and run?

1. Install Ollama: Windows|MacOS
2. Install Personal-Productivity-Assistant: Windows|MacOS
3. First start can take some, due to the fact that of deepseek-r1:14 b (14 billion params, experienciacortazar.com.ar chain of thoughts).
4. Once installed, a black circle will appear in the system tray:.
5. Now do your regular work and wait some time to gather excellent quantity of stats. Application will keep amount of 2nd you invest in each application or website.

6. Finally create the report.

Note: Generating the report requires a minimum of 9GB of RAM, and the process might take a few minutes. If memory usage is an issue, it's possible to switch to a smaller model for more effective resource management.

I 'd like to hear your feedback! Whether it's feature demands, bug reports, or your success stories, sign up with the neighborhood on GitHub to contribute and help make the tool even better. Together, we can form the future of efficiency tools. Check it out here!

GitHub - smelnyk/Personal-Productivity-Assistant: Personal Productivity Assistant is a.

Personal Productivity Assistant is a revolutionary open-source application devoting to enhancing individuals focus ...

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About Me

I'm Serhii Melnyk, with over 16 years of experience in creating and implementing high-reliability, scalable, and top quality tasks. My technical expertise is complemented by strong team-leading and interaction abilities, which have assisted me effectively lead teams for canadasimple.com over 5 years.

Throughout my career, I've concentrated on creating workflows for artificial intelligence and data science API services in cloud infrastructure, in addition to designing monolithic and Kubernetes (K8S) containerized microservices architectures. I have actually likewise worked thoroughly with high-load SaaS options, REST/GRPC API executions, and CI/CD pipeline design.

I'm enthusiastic about item shipment, it-viking.ch and my background includes mentoring staff member, performing extensive code and design evaluations, and handling people. Additionally, I have actually worked with AWS Cloud services, as well as GCP and Azure combinations.