Am mai dat de o problema destul de mare:
Daca folosesti ceva librarie nou nouta, e.g. tRPC, nu te va ajuta ChatGPT sau iti va da raspunsul pentru o versiune mai veche 
Inca nu s-a inventat in 2021
De ce l-au facut atat de submissive si overly polite 
mincinos mic :))
The new subscription plan, ChatGPT Plus, will be available for $20/month, and subscribers will receive a number of benefits:
- General access to ChatGPT, even during peak times
- Faster response times
- Priority access to new features and improvements
Ultimul update a ChatGPT este 30 ianuarie.
Umblă zvonuri că Google pregătește să deschidă accesul public la LaMDA.
Google mai are si PaLM, care e mai capabil chiar.
Diferența e ca LaMDA e antrenat pentru dialog, așa cum e ChatGPT, iar PaLM are alte aptitudini, așa cum pentru OpenAI este GPT-3.
LaMDA e modelul despre care un fost angajat Google a spus că e “sentient”.
Cica s-a intors Sergey Brin la Google si incepe sa scrie cod pentru partea de AI.
Behind the new chatbot is LaMDA, Google’s AI that generated text with such skill that a company engineer last year called it sentient, a claim the technology giant and scientists widely dismissed.
Microsoft has said it plans to imbue AI into its all its products and on Tuesday plans to brief news outlets on developments it did not specify, with its CEO Satya Nadella, according to an invitation seen by Reuters. Sam Altman, the CEO of OpenAI, tweeted that he would also attend the event.
Este in spate cu vreo 2 luni 
frige scaunul la Google, in sfarsit ii mai trezeste un pic de concurenta
Integrare ChatGPT in motor de cautare Bing si browser Edge.
Introducing your copilot for the web: AI-powered Bing and Microsoft Edge
Un catalog cu tot felul de applicatii AI:
Cum spunea cineva, in dev va fi un “AI first”, așa cum era “mobile first” acum 10 ani.
ChatGPT este integrat acuma in motorul de cautare Bing si browser Edge, m-am adaugat pe waitlist, sunt niste demo-uri in video din postul meu anterior pe acest thread mindblowing, game changer. Google cica a pierdut 100 mil dupa ce in postarea lor chat-ul dadea un raspuns gresit.
Am primit access la motorul de cautare Bing cu ChatGPT integrat, m-am jucat un pic cu el:
Searching for:
artificial intelligenceSearching for:
artificial intelligenceGenerating answers for you…
Generating answers for you…
Artificial intelligence (AI) is the ability of a computer or a robot to perform tasks that normally require human intelligence1. Some examples of AI tasks are speech recognition, computer vision, natural language translation and reasoning2. There are different types and levels of AI, such as artificial general intelligence (AGI), which is a hypothetical form of AI that would have human-like intelligence and consciousness3.
Received message. Artificial intelligence (AI) is the ability of a computer or a robot to perform tasks that normally require human intelligence. Some examples of AI tasks are speech recognition, computer vision, natural language translation and reasoning. There are different types and levels of AI, such as artificial general intelligence (AGI), which is a hypothetical form of AI that would have human-like intelligence and consciousness.
Learn more:1. britannica.com2. en.wikipedia.org3. ibm.com
How does AI work?
Sent message. How does AI work?
Searching for:
how does AI workSearching for:
how does AI workGenerating answers for you…
Generating answers for you…
AI works by using algorithms to discover patterns and generate insights from data1. Machine learning and deep learning are two subcategories of AI that allow machines to learn from data and model human intelligence2. Machine learning requires some human intervention to tell the machine how to extract features from data, while deep learning uses artificial neural networks that can learn features automatically34.
Received message. AI works by using algorithms to discover patterns and generate insights from data. Machine learning and deep learning are two subcategories of AI that allow machines to learn from data and model human intelligence. Machine learning requires some human intervention to tell the machine how to extract features from data, while deep learning uses artificial neural networks that can learn features automatically .
Learn more:1. simplilearn.com2. builtin.com3. csuglobal.edu4. eib.org
What are some examples of machine learning and deep learning?
Sent message. What are some examples of machine learning and deep learning?
Searching for:
examples of machine learning and deep learningSearching for:
examples of machine learning and deep learningGenerating answers for you…
Generating answers for you…
Some examples of machine learning are:
- Computer vision, which is used for facial recognition, fingerprint recognition, or vehicle identification1.
- Information retrieval, which is used for text search or image search1.
- Automated email marketing, which targets specific customers based on their preferences1.
- Medical diagnosis, which detects cancer tumors or other diseases based on symptoms1.
Some examples of deep learning are:
- Natural language processing, which is used for speech recognition, text generation, or machine translation2.
- Image generation, which can create realistic images of faces, animals, or landscapes2.
- Reinforcement learning, which can train agents to play games or perform tasks by rewarding them for good actions2.
Received message. Some examples of machine learning are: - Computer vision, which is used for facial recognition, fingerprint recognition, or vehicle identification. - Information retrieval, which is used for text search or image search. - Automated email marketing, which targets specific customers based on their preferences. - Medical diagnosis, which detects cancer tumors or other diseases based on symptoms. Some examples of deep learning are: - Natural language processing, which is used for speech recognition, text generation, or machine translation. - Image generation, which can create realistic images of faces, animals, or landscapes. - Reinforcement learning, which can train agents to play games or perform tasks by rewarding them for good actions.
Learn more:1. tutorialspoint.com2. zendesk.com3. learn.microsoft.com4. codecademy.com
How can I use machine learning and deep learning in my own projects?
Sent message. How can I use machine learning and deep learning in my own projects?
Searching for:
how to use machine learning and deep learning in projectsSearching for:
how to use machine learning and deep learning in projectsGenerating answers for you…
Generating answers for you…
You can use machine learning and deep learning in your own projects depending on your goals, data, and resources. Machine learning is more suitable for projects that involve simple or structured data, such as numerical or categorical data1. Some examples of machine learning projects are:
- Skin disease detection system using CNN2.
- Signature verification system using CNN2.
- Heart failure prediction system2.
- Credit card fraud detection system2.
Deep learning is more complex and is typically used for projects that involve unstructured or spatial data, such as images, audio, or text1. Some examples of deep learning projects are:
- Yoga poses detection using OpenPose2.
- Automatic pronunciation mistake detector2.
- Learning disability detector and classifier system2.
- AI mental health therapist chatbot2.
To use machine learning and deep learning in your own projects, you will need some tools or frameworks that can help you implement the algorithms and models. Some popular tools or frameworks are:
- Python: a general-purpose programming language that has many libraries for machine learning and deep learning, such as TensorFlow, PyTorch, Scikit-learn, Keras, etc.3
- R: a statistical programming language that has many packages for machine learning and deep learning, such as Caret, MLR, H2O.ai, MXNet etc.3
- MATLAB: a numerical computing environment that has many toolboxes for machine learning and deep learning, such as Statistics and Machine Learning Toolbox™️ , Deep Learning Toolbox™️ , Computer Vision Toolbox™️ , etc.3
Received message. You can use machine learning and deep learning in your own projects depending on your goals, data, and resources. Machine learning is more suitable for projects that involve simple or structured data, such as numerical or categorical data. Some examples of machine learning projects are: - Skin disease detection system using CNN. - Signature verification system using CNN. - Heart failure prediction system. - Credit card fraud detection system. Deep learning is more complex and is typically used for projects that involve unstructured or spatial data, such as images, audio, or text. Some examples of deep learning projects are: - Yoga poses detection using OpenPose. - Automatic pronunciation mistake detector. - Learning disability detector and classifier system. - AI mental health therapist chatbot. To use machine learning and deep learning in your own projects, you will need some tools or frameworks that can help you implement the algorithms and models. Some popular tools or frameworks are: - Python: a general-purpose programming language that has many libraries for machine learning and deep learning, such as TensorFlow, PyTorch, Scikit-learn, Keras, etc. - R: a statistical programming language that has many packages for machine learning and deep learning, such as Caret, MLR, H2O.ai, MXNet etc. - MATLAB: a numerical computing environment that has many toolboxes for machine learning and deep learning, such as Statistics and Machine Learning Toolbox™️ , Deep Learning Toolbox™️ , Computer Vision Toolbox™️ , etc.
Learn more:1. embeddedcomputing.com2. nevonprojects.com3. springboard.com
Which tool or framework do you recommend for beginners?
Sent message. Which tool or framework do you recommend for beginners?
There is no definitive answer to which tool or framework is best for beginners, as different tools or frameworks may have different advantages and disadvantages depending on the project and the user’s preferences. However, some general factors that may influence the choice of tool or framework are:
- The availability and quality of documentation, tutorials, and community support.
- The ease of installation and use.
- The compatibility and integration with other tools or frameworks.
- The performance and scalability of the tool or framework.
Based on these factors, some popular choices for beginners are:
- Python with TensorFlow or PyTorch: Python is a widely used programming language that has many libraries for machine learning and deep learning. TensorFlow and PyTorch are two of the most popular frameworks for deep learning that offer high-level APIs and low-level control. They also have good documentation, tutorials, and community support.
- R with Caret or MLR: R is a statistical programming language that has many packages for machine learning and deep learning. Caret and MLR are two packages that provide a unified interface to various machine learning algorithms. They also have good documentation, tutorials, and community support.
- MATLAB with Statistics and Machine Learning Toolbox or Deep Learning Toolbox: MATLAB is a numerical computing environment that has many toolboxes for machine learning and deep learning. Statistics and Machine Learning Toolbox™️ provides functions and apps to perform various machine learning tasks. Deep Learning Toolbox™️ provides functions and apps to design, train, visualize, test deep neural networks. They also have good documentation, tutorials, and community support.
Received message. There is no definitive answer to which tool or framework is best for beginners, as different tools or frameworks may have different advantages and disadvantages depending on the project and the user’s preferences. However, some general factors that may influence the choice of tool or framework are: - The availability and quality of documentation, tutorials, and community support. - The ease of installation and use. - The compatibility and integration with other tools or frameworks. - The performance and scalability of the tool or framework. Based on these factors, some popular choices for beginners are: - Python with TensorFlow or PyTorch: Python is a widely used programming language that has many libraries for machine learning and deep learning. TensorFlow and PyTorch are two of the most popular frameworks for deep learning that offer high-level APIs and low-level control. They also have good documentation, tutorials, and community support. - R with Caret or MLR: R is a statistical programming language that has many packages for machine learning and deep learning. Caret and MLR are two packages that provide a unified interface to various machine learning algorithms. They also have good documentation, tutorials, and community support. - MATLAB with Statistics and Machine Learning Toolbox or Deep Learning Toolbox: MATLAB is a numerical computing environment that has many toolboxes for machine learning and deep learning. Statistics and Machine Learning Toolbox™️ provides functions and apps to perform various machine learning tasks. Deep Learning Toolbox™️ provides functions and apps to design, train, visualize, test deep neural networks. They also have good documentation, tutorials, and community support.
What are some online courses or books on machine learning and deep learning?
Sent message. What are some online courses or books on machine learning and deep learning?
Searching for:
online courses or books on machine learning and deep learningSearching for:
online courses or books on machine learning and deep learningGenerating answers for you…
Generating answers for you…
There are many online courses or books on machine learning and deep learning that you can choose from depending on your level, interest, and goal. Some examples are:
- Data Science: The Art of Data Science by Roger D Peng and Elizabeth Matsui1. This book introduces the principles and practices of data science, including how to formulate questions, collect and analyze data, and communicate findings.
- Machine Learning: Machine Learning by Andrew Ng2. This course covers the theory and practice of machine learning, including supervised learning, unsupervised learning, neural networks, support vector machines, etc.
- Deep Learning: Deep Learning by Ian Goodfellow and Yoshua Bengio1. This book provides a comprehensive introduction to deep learning, covering topics such as linear algebra, optimization, convolutional networks, recurrent networks, generative models etc.
- TensorFlow: DeepLearning.AI TensorFlow Developer by Laurence Moroney2. This course teaches how to use TensorFlow to build and train various types of neural networks for computer vision, natural language processing etc.
Received message. There are many online courses or books on machine learning and deep learning that you can choose from depending on your level, interest, and goal. Some examples are: - Data Science: The Art of Data Science by Roger D Peng and Elizabeth Matsui. This book introduces the principles and practices of data science, including how to formulate questions, collect and analyze data, and communicate findings. - Machine Learning: Machine Learning by Andrew Ng. This course covers the theory and practice of machine learning, including supervised learning, unsupervised learning, neural networks, support vector machines, etc. - Deep Learning: Deep Learning by Ian Goodfellow and Yoshua Bengio. This book provides a comprehensive introduction to deep learning, covering topics such as linear algebra, optimization, convolutional networks, recurrent networks, generative models etc. - TensorFlow: DeepLearning.AI TensorFlow Developer by Laurence Moroney. This course teaches how to use TensorFlow to build and train various types of neural networks for computer vision, natural language processing etc.
Learn more:1. vitalflux.com2. coursera.org3. online.stanford.edu4. coursera.org
Un nou feature in Bing cu ChatGPT:
Si o integrare mai buna cu Windows 11:
Now, you can access the world’s information and generate content from the Windows taskbar, providing you with an AI copilot directly on your desktop. If you are currently in the preview, these features will be available to you by downloading the latest Windows update rolling out today. Find this update in the Windows Update settings menu*
Ii schimbă temperatura probabil