Gemini Live: This feature, leveraging Project Astra, rolled out on Android and iOS already, allowing real-time conversations with Gemini about what's on the screen or through the phone's camera. It's also being integrated more deeply into Google apps for tasks like getting directions from Maps.
๐ t.me/techpsyche
๐ t.me/techpsyche
๐1
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Project Astra _ How Visual Interpreter Helps People who are Blind and Low-Vision Navigate the World
๐ t.me/techpsyche
๐ t.me/techpsyche
AI Mode on Google Search: This new AI-powered Search will allow users to ask longer questions and offer more interactive, personalized, and visually rich results, including AI-generated graphs for complex queries and a "try it on" feature for apparel shopping, which will allow users to virtually try clothing before they shop.
Search Live: Utilizing Project Astra capabilities, this feature will allow users to ask questions about what their camera sees. Coming to AI Mode on Google Search, this summer.
๐ t.me/techpsyche
Search Live: Utilizing Project Astra capabilities, this feature will allow users to ask questions about what their camera sees. Coming to AI Mode on Google Search, this summer.
๐ t.me/techpsyche
Flow: A new AI filmmaking tool that combines Imagen 4 and Veo 3, offering features like camera movement and perspective controls, scene extension, and integration of AI-generated video with music from Google Lyria.
๐ t.me/techpsyche
๐ t.me/techpsyche
๐1
Google I/O Keynote 2025 Summary: Advancements in AI, Search, and XR.
### TPU Updates
- Ironwood 7th Generation TPU(Tensor Processing Unit): Designed to power thinking and inference at scale with 10X performance over previous generation. Coming to Google Cloud customers later this year.
### Gemini AI Updates:
Update: Gemini Now Has over 400M monthly users.
- Gemini 2.5 Pro: Optimized for quality and complex tasks. It includes an enhanced reasoning mode called *Deep Think*
- Gemini 2.5 Flash: optimized for speed and cost-efficiency, particularly for high-volume applications.
- Jules: Google's AI Coding Agent. Jules autonomously reads your code performs tasks like writing tests and fixing bugs. jules.google
- Gemini Live: This feature, leveraging Project Astra, rolled out on Android and iOS already, allowing real-time conversations with Gemini about what's on the screen or through the phone's camera. Details & Demo Here ๐ t.me/techpsyche/1080
- Imagen 4: Google's next-generation text-to-image model was unveiled, producing visuals with greater detail and improved text rendering within images. It's rolling out in the Gemini app.
- Veo 3: The newest text-to-video model can now generate fluid motion graphics. with better visual quality, native audio generation, soundtracks, sound effects that match the visuals, and dialogue.
- Flow: A new AI filmmaking tool that combines Imagen 4 and Veo 3, offering features like camera movement and perspective controls, scene extension, and integration of AI-generated video with music from Google Lyria. Details and Demo Here ๐ t.me/techpsyche/1085
- Music AI Sandbox: For creating music tracks, spark new creative possibilities and help artists explore unique musical ideas.
- Lyria 2: Improved Music generation, Can do rich classical music and add quality vocals.
- Gemini App Enhancements: The app is getting an *Agent Mode* to retrieve and summarize web data in real time for multi-step tasks.
- Gemini in Chrome: Your AI Assistant on the web. It will understand the content of your current page and you can ask it anything based on your current page or even summarize for you.
### AI in Search:
Update: Google Lens now has over 1.5B monthly users.
- AI Mode on Google Search: This new AI-powered Search will allow users to ask longer questions and offer more interactive, personalized, and visually rich results, including AI-generated graphs for complex queries and a "try it on" feature for apparel shopping, which will allow users to virtually try clothing before they shop. Details & Demo Here ๐ t.me/techpsyche/1083
- Personalization in Search: AI Mode will incorporate past searches and connect with other Google services like Gmail for more contextual results.
- Deep Research Upgrade: Users will be able to upload files and images for more contextual and detailed responses. It's also being integrated with Canvas for creating dynamic infographics, website, podcast and more. Canvas is just next to Deep Research on Gemini.
- Search Live: Utilizing Project Astra capabilities, this feature will allow users to ask questions about what their camera sees. Coming to AI Mode on Google Search, this summer. Details & Demo Here ๐ t.me/techpsyche/1083
### Android XR:
In patnership with Samsung(Project Moohan) and Qualcomm
- Google previewed its evolving Android XR platform for headsets and smart glasses with camera, speaker, microphone and Gemini, demonstrating smart glasses for messaging, navigation, and real-time language translation using built-in lens displays.
- Google has partnered with eyewear brands, Gentle Monster and Warby Parker will be the first to develop Android XR-based smart glasses.
- A demo showcased live language translation on Android XR glasses.
### Agentic AI:
Through Project Mariner, Google demonstrated agentic AI systems that can perform multi-step tasks like booking tickets or making online purchases autonomously.
### TPU Updates
- Ironwood 7th Generation TPU(Tensor Processing Unit): Designed to power thinking and inference at scale with 10X performance over previous generation. Coming to Google Cloud customers later this year.
### Gemini AI Updates:
Update: Gemini Now Has over 400M monthly users.
- Gemini 2.5 Pro: Optimized for quality and complex tasks. It includes an enhanced reasoning mode called *Deep Think*
- Gemini 2.5 Flash: optimized for speed and cost-efficiency, particularly for high-volume applications.
- Jules: Google's AI Coding Agent. Jules autonomously reads your code performs tasks like writing tests and fixing bugs. jules.google
- Gemini Live: This feature, leveraging Project Astra, rolled out on Android and iOS already, allowing real-time conversations with Gemini about what's on the screen or through the phone's camera. Details & Demo Here ๐ t.me/techpsyche/1080
- Imagen 4: Google's next-generation text-to-image model was unveiled, producing visuals with greater detail and improved text rendering within images. It's rolling out in the Gemini app.
- Veo 3: The newest text-to-video model can now generate fluid motion graphics. with better visual quality, native audio generation, soundtracks, sound effects that match the visuals, and dialogue.
- Flow: A new AI filmmaking tool that combines Imagen 4 and Veo 3, offering features like camera movement and perspective controls, scene extension, and integration of AI-generated video with music from Google Lyria. Details and Demo Here ๐ t.me/techpsyche/1085
- Music AI Sandbox: For creating music tracks, spark new creative possibilities and help artists explore unique musical ideas.
- Lyria 2: Improved Music generation, Can do rich classical music and add quality vocals.
- Gemini App Enhancements: The app is getting an *Agent Mode* to retrieve and summarize web data in real time for multi-step tasks.
- Gemini in Chrome: Your AI Assistant on the web. It will understand the content of your current page and you can ask it anything based on your current page or even summarize for you.
### AI in Search:
Update: Google Lens now has over 1.5B monthly users.
- AI Mode on Google Search: This new AI-powered Search will allow users to ask longer questions and offer more interactive, personalized, and visually rich results, including AI-generated graphs for complex queries and a "try it on" feature for apparel shopping, which will allow users to virtually try clothing before they shop. Details & Demo Here ๐ t.me/techpsyche/1083
- Personalization in Search: AI Mode will incorporate past searches and connect with other Google services like Gmail for more contextual results.
- Deep Research Upgrade: Users will be able to upload files and images for more contextual and detailed responses. It's also being integrated with Canvas for creating dynamic infographics, website, podcast and more. Canvas is just next to Deep Research on Gemini.
- Search Live: Utilizing Project Astra capabilities, this feature will allow users to ask questions about what their camera sees. Coming to AI Mode on Google Search, this summer. Details & Demo Here ๐ t.me/techpsyche/1083
### Android XR:
In patnership with Samsung(Project Moohan) and Qualcomm
- Google previewed its evolving Android XR platform for headsets and smart glasses with camera, speaker, microphone and Gemini, demonstrating smart glasses for messaging, navigation, and real-time language translation using built-in lens displays.
- Google has partnered with eyewear brands, Gentle Monster and Warby Parker will be the first to develop Android XR-based smart glasses.
- A demo showcased live language translation on Android XR glasses.
### Agentic AI:
Through Project Mariner, Google demonstrated agentic AI systems that can perform multi-step tasks like booking tickets or making online purchases autonomously.
๐1
### Google Beam:
- Through Project Starline, Google Beam is a new 3D teleconferencing technology using a six-camera array and a custom light field display for realistic 3D representations during calls.
### Other Notable Announcements:
- Firesat: A partnership led by Earth Fire Alliance to use AI to create a breakthrough in wildfire detection. FireSat uses high-res multispectral satellite imagery and AI to provide near real-time insights on wildfires. Provides global high resolution imagery that is updates in every 20 minutes.
- SynthID Detector: A new portal to help identify AI-generated content in images, audio, video, and text by scanning for the SynthID watermark.
- Google AI Ultra: A new subscription plan offering the highest access to Google's most capable AI models and premium features.
- Personalized Smart Replies in Gmail: Gemini models can now generate smart replies tailored to your writing style by learning from your emails and Drive documents (with your permission).
- Real-time Translation in Google Meet: This feature can translate speech in near real-time, matching the speaker's voice, tone, and expressions. English and Spanish translation is rolling out in beta for Google AI Pro and Ultra subscribers.
- Chrome Password Manager Upgrade: It will automatically change passwords on accounts compromised in data breaches.
These were some of the major announcements from yesterday's Google I/O Keynote. The event continues today with more developer-focused sessions.
Follow Tech Psyche for more updates.
Also follow Our WhatsApp Channel
- Through Project Starline, Google Beam is a new 3D teleconferencing technology using a six-camera array and a custom light field display for realistic 3D representations during calls.
### Other Notable Announcements:
- Firesat: A partnership led by Earth Fire Alliance to use AI to create a breakthrough in wildfire detection. FireSat uses high-res multispectral satellite imagery and AI to provide near real-time insights on wildfires. Provides global high resolution imagery that is updates in every 20 minutes.
- SynthID Detector: A new portal to help identify AI-generated content in images, audio, video, and text by scanning for the SynthID watermark.
- Google AI Ultra: A new subscription plan offering the highest access to Google's most capable AI models and premium features.
- Personalized Smart Replies in Gmail: Gemini models can now generate smart replies tailored to your writing style by learning from your emails and Drive documents (with your permission).
- Real-time Translation in Google Meet: This feature can translate speech in near real-time, matching the speaker's voice, tone, and expressions. English and Spanish translation is rolling out in beta for Google AI Pro and Ultra subscribers.
- Chrome Password Manager Upgrade: It will automatically change passwords on accounts compromised in data breaches.
These were some of the major announcements from yesterday's Google I/O Keynote. The event continues today with more developer-focused sessions.
Follow Tech Psyche for more updates.
Also follow Our WhatsApp Channel
๐1
Types of Stablecoins
Today, weโll tell you about the three main categories of stablecoins.
โช๏ธ Stablecoins backed by fiat currencies
These coins are backed by real-life assets, fiat money, or paper money. Two examples of this stablecoin are Tether (USDT) and USD Coin (USDC). The companies issuing these coins own large reserves to support every issued coin; however, Tether has come under intense scrutiny in the past for this specific issue.
โช๏ธ Stablecoins backed by cryptocurrencies
Some projects are so bold that theyโre willing to back their stablecoin with other cryptocurrencies (not real assets or money). For example, a crypto-backed stablecoin with a value of $1 could be supported by a crypto asset worth $2. The logic here is that if the underlying assetโs value were to drop, the stablecoin would still be able to maintain its dollar peg.
The most famous crypto-backed stablecoin is Dai (DAI).
โช๏ธ Algorithmic stablecoins
Algorithmic stablecoins are not backed by assets or fiat currencies, which makes it difficult to understand why or how theyโre stablecoins in the first place. As their name indicates, the value of these coins is controlled by computer algorithms. If the stablecoinโs value is pegged to $1 but rises above $1, the code will automatically mint and release more coins into circulation to lower the stablecoinโs value back to $1. Conversely, if the value drops below $1, the algorithm will removeโor burnโcoins from circulation to lift the value back up to $1. The amount of coins you hold will change, but theyโll always reflect the value you own.
Please note: Stablecoins are not dollarsโtheyโre cryptocurrencies. Even when dealing with stablecoins, investing in crypto carries inherent risksโcase in point the collapse of Terraโs algorithmic stablecoin TerraUSD.
Non-Recourse Loans in Crypto: https://t.me/techpsyche/756
Funding in Crypto Trading: https://t.me/techpsyche/766
Choosing the right Exchange: https://t.me/techpsyche/774
More Resources Here:
https://whatsapp.com/channel/0029VajB00n0LKZ7cSloGR1M
#crypto #web3 #blockchain #finance #stocks
Today, weโll tell you about the three main categories of stablecoins.
โช๏ธ Stablecoins backed by fiat currencies
These coins are backed by real-life assets, fiat money, or paper money. Two examples of this stablecoin are Tether (USDT) and USD Coin (USDC). The companies issuing these coins own large reserves to support every issued coin; however, Tether has come under intense scrutiny in the past for this specific issue.
โช๏ธ Stablecoins backed by cryptocurrencies
Some projects are so bold that theyโre willing to back their stablecoin with other cryptocurrencies (not real assets or money). For example, a crypto-backed stablecoin with a value of $1 could be supported by a crypto asset worth $2. The logic here is that if the underlying assetโs value were to drop, the stablecoin would still be able to maintain its dollar peg.
The most famous crypto-backed stablecoin is Dai (DAI).
โช๏ธ Algorithmic stablecoins
Algorithmic stablecoins are not backed by assets or fiat currencies, which makes it difficult to understand why or how theyโre stablecoins in the first place. As their name indicates, the value of these coins is controlled by computer algorithms. If the stablecoinโs value is pegged to $1 but rises above $1, the code will automatically mint and release more coins into circulation to lower the stablecoinโs value back to $1. Conversely, if the value drops below $1, the algorithm will removeโor burnโcoins from circulation to lift the value back up to $1. The amount of coins you hold will change, but theyโll always reflect the value you own.
Please note: Stablecoins are not dollarsโtheyโre cryptocurrencies. Even when dealing with stablecoins, investing in crypto carries inherent risksโcase in point the collapse of Terraโs algorithmic stablecoin TerraUSD.
Non-Recourse Loans in Crypto: https://t.me/techpsyche/756
Funding in Crypto Trading: https://t.me/techpsyche/766
Choosing the right Exchange: https://t.me/techpsyche/774
More Resources Here:
https://whatsapp.com/channel/0029VajB00n0LKZ7cSloGR1M
#crypto #web3 #blockchain #finance #stocks
Forwarded from Artificial Intelligence Resources TP . AI Tools . AI Updates
๐๐จ๐ฐ ๐ญ๐จ ๐๐๐ฌ๐ข๐ ๐ง ๐ ๐๐๐ฎ๐ซ๐๐ฅ ๐๐๐ญ๐ฐ๐จ๐ซ๐ค
โ ๐๐๐๐ข๐ง๐ ๐ญ๐ก๐ ๐๐ซ๐จ๐๐ฅ๐๐ฆ
Clearly outline the type of task:
โฌ Classification: Predict discrete labels (e.g., cats vs dogs).
โฌ Regression: Predict continuous values
โฌ Clustering: Find patterns in unsupervised data.
โ ๐๐ซ๐๐ฉ๐ซ๐จ๐๐๐ฌ๐ฌ ๐๐๐ญ๐
Data quality is critical for model performance.
โฌ Normalize and standardize features MinMaxScaler, StandardScaler.
โฌ Handle missing values and outliers.
โฌ Split your data: Training (70%), Validation (15%), Testing (15%).
โ ๐๐๐ฌ๐ข๐ ๐ง ๐ญ๐ก๐ ๐๐๐ญ๐ฐ๐จ๐ซ๐ค ๐๐ซ๐๐ก๐ข๐ญ๐๐๐ญ๐ฎ๐ซ๐
๐ฐ๐ง๐ฉ๐ฎ๐ญ ๐๐๐ฒ๐๐ซ
โฌ Number of neurons equals the input features.
๐๐ข๐๐๐๐ง ๐๐๐ฒ๐๐ซ๐ฌ
โฌ Start with a few layers and increase as needed.
โฌ Use activation functions:
โ ReLU: General-purpose. Fast and efficient.
โ Leaky ReLU: Fixes dying neuron problems.
โ Tanh/Sigmoid: Use sparingly for specific cases.
๐๐ฎ๐ญ๐ฉ๐ฎ๐ญ ๐๐๐ฒ๐๐ซ
โฌ Classification: Use Softmax or Sigmoid for probability outputs.
โฌ Regression: Linear activation (no activation applied).
โ ๐๐ง๐ข๐ญ๐ข๐๐ฅ๐ข๐ณ๐ ๐๐๐ข๐ ๐ก๐ญ๐ฌ
Proper weight initialization helps in faster convergence:
โฌ He Initialization: Best for ReLU-based activations.
โฌ Xavier Initialization: Ideal for sigmoid/tanh activations.
โ ๐๐ก๐จ๐จ๐ฌ๐ ๐ญ๐ก๐ ๐๐จ๐ฌ๐ฌ ๐ ๐ฎ๐ง๐๐ญ๐ข๐จ๐ง
โฌ Classification: Cross-Entropy Loss.
โฌ Regression: Mean Squared Error or Mean Absolute Error.
โ ๐๐๐ฅ๐๐๐ญ ๐ญ๐ก๐ ๐๐ฉ๐ญ๐ข๐ฆ๐ข๐ณ๐๐ซ
Pick the right optimizer to minimize the loss:
โฌ Adam: Most popular choice for speed and stability.
โฌ SGD: Slower but reliable for smaller models.
โ ๐๐ฉ๐๐๐ข๐๐ฒ ๐๐ฉ๐จ๐๐ก๐ฌ ๐๐ง๐ ๐๐๐ญ๐๐ก ๐๐ข๐ณ๐
โฌ Epochs: Define total passes over the training set. Start with 50โ100 epochs.
โฌ Batch Size: Small batches train faster but are less stable. Larger batches stabilize gradients.
โ ๐๐ซ๐๐ฏ๐๐ง๐ญ ๐๐ฏ๐๐ซ๐๐ข๐ญ๐ญ๐ข๐ง๐
โฌ Add Dropout Layers to randomly deactivate neurons.
โฌ Use L2 Regularization to penalize large weights.
โ ๐๐ฒ๐ฉ๐๐ซ๐ฉ๐๐ซ๐๐ฆ๐๐ญ๐๐ซ ๐๐ฎ๐ง๐ข๐ง๐
Optimize your model parameters to improve performance:
โฌ Adjust learning rate, dropout rate, layer size, and activations.
โฌ Use Grid Search or Random Search for hyperparameter optimization.
โ ๐๐ฏ๐๐ฅ๐ฎ๐๐ญ๐ ๐๐ง๐ ๐๐ฆ๐ฉ๐ซ๐จ๐ฏ๐
โฌ Monitor metrics for performance:
โ Classification: Accuracy, Precision, Recall, F1-score, AUC-ROC.
โ Regression: RMSE, MAE, Rยฒ score.
โ ๐๐๐ญ๐ ๐๐ฎ๐ ๐ฆ๐๐ง๐ญ๐๐ญ๐ข๐จ๐ง
โฌ For image tasks, apply transformations like rotation, scaling, and flipping to expand your dataset.
Neural Networks Overview: https://t.me/airesourcestp/119
AI & ML Free Courses by Top Institutions: https://t.me/airesourcestp/100
5 Free NLP Courses
https://t.me/airesourcestp/110
Best Courses for AI from Universities with YouTube Playlists
https://t.me/airesourcestp/111
Like if you want me to continue data science series ๐โค๏ธ
More Resources Here:
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
ENJOY LEARNING ๐๐
โ ๐๐๐๐ข๐ง๐ ๐ญ๐ก๐ ๐๐ซ๐จ๐๐ฅ๐๐ฆ
Clearly outline the type of task:
โฌ Classification: Predict discrete labels (e.g., cats vs dogs).
โฌ Regression: Predict continuous values
โฌ Clustering: Find patterns in unsupervised data.
โ ๐๐ซ๐๐ฉ๐ซ๐จ๐๐๐ฌ๐ฌ ๐๐๐ญ๐
Data quality is critical for model performance.
โฌ Normalize and standardize features MinMaxScaler, StandardScaler.
โฌ Handle missing values and outliers.
โฌ Split your data: Training (70%), Validation (15%), Testing (15%).
โ ๐๐๐ฌ๐ข๐ ๐ง ๐ญ๐ก๐ ๐๐๐ญ๐ฐ๐จ๐ซ๐ค ๐๐ซ๐๐ก๐ข๐ญ๐๐๐ญ๐ฎ๐ซ๐
๐ฐ๐ง๐ฉ๐ฎ๐ญ ๐๐๐ฒ๐๐ซ
โฌ Number of neurons equals the input features.
๐๐ข๐๐๐๐ง ๐๐๐ฒ๐๐ซ๐ฌ
โฌ Start with a few layers and increase as needed.
โฌ Use activation functions:
โ ReLU: General-purpose. Fast and efficient.
โ Leaky ReLU: Fixes dying neuron problems.
โ Tanh/Sigmoid: Use sparingly for specific cases.
๐๐ฎ๐ญ๐ฉ๐ฎ๐ญ ๐๐๐ฒ๐๐ซ
โฌ Classification: Use Softmax or Sigmoid for probability outputs.
โฌ Regression: Linear activation (no activation applied).
โ ๐๐ง๐ข๐ญ๐ข๐๐ฅ๐ข๐ณ๐ ๐๐๐ข๐ ๐ก๐ญ๐ฌ
Proper weight initialization helps in faster convergence:
โฌ He Initialization: Best for ReLU-based activations.
โฌ Xavier Initialization: Ideal for sigmoid/tanh activations.
โ ๐๐ก๐จ๐จ๐ฌ๐ ๐ญ๐ก๐ ๐๐จ๐ฌ๐ฌ ๐ ๐ฎ๐ง๐๐ญ๐ข๐จ๐ง
โฌ Classification: Cross-Entropy Loss.
โฌ Regression: Mean Squared Error or Mean Absolute Error.
โ ๐๐๐ฅ๐๐๐ญ ๐ญ๐ก๐ ๐๐ฉ๐ญ๐ข๐ฆ๐ข๐ณ๐๐ซ
Pick the right optimizer to minimize the loss:
โฌ Adam: Most popular choice for speed and stability.
โฌ SGD: Slower but reliable for smaller models.
โ ๐๐ฉ๐๐๐ข๐๐ฒ ๐๐ฉ๐จ๐๐ก๐ฌ ๐๐ง๐ ๐๐๐ญ๐๐ก ๐๐ข๐ณ๐
โฌ Epochs: Define total passes over the training set. Start with 50โ100 epochs.
โฌ Batch Size: Small batches train faster but are less stable. Larger batches stabilize gradients.
โ ๐๐ซ๐๐ฏ๐๐ง๐ญ ๐๐ฏ๐๐ซ๐๐ข๐ญ๐ญ๐ข๐ง๐
โฌ Add Dropout Layers to randomly deactivate neurons.
โฌ Use L2 Regularization to penalize large weights.
โ ๐๐ฒ๐ฉ๐๐ซ๐ฉ๐๐ซ๐๐ฆ๐๐ญ๐๐ซ ๐๐ฎ๐ง๐ข๐ง๐
Optimize your model parameters to improve performance:
โฌ Adjust learning rate, dropout rate, layer size, and activations.
โฌ Use Grid Search or Random Search for hyperparameter optimization.
โ ๐๐ฏ๐๐ฅ๐ฎ๐๐ญ๐ ๐๐ง๐ ๐๐ฆ๐ฉ๐ซ๐จ๐ฏ๐
โฌ Monitor metrics for performance:
โ Classification: Accuracy, Precision, Recall, F1-score, AUC-ROC.
โ Regression: RMSE, MAE, Rยฒ score.
โ ๐๐๐ญ๐ ๐๐ฎ๐ ๐ฆ๐๐ง๐ญ๐๐ญ๐ข๐จ๐ง
โฌ For image tasks, apply transformations like rotation, scaling, and flipping to expand your dataset.
Neural Networks Overview: https://t.me/airesourcestp/119
AI & ML Free Courses by Top Institutions: https://t.me/airesourcestp/100
5 Free NLP Courses
https://t.me/airesourcestp/110
Best Courses for AI from Universities with YouTube Playlists
https://t.me/airesourcestp/111
Like if you want me to continue data science series ๐โค๏ธ
More Resources Here:
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
ENJOY LEARNING ๐๐
โค1๐1
๐ค AI wins debates against humans, with bonus points for knowing your personal details
New research reveals that AI can be just as persuasive as humans in debates, and even more so when armed with information about a personโs age, gender, ethnicity, and political views. Francesco Salvi, a researcher at the Swiss Federal Institute of Technology, warns that if persuasive AI can be deployed at scale, it could lead to armies of bots microtargeting undecided voters with tailored political narratives that feel authentic.
The study, which involved 600 debates, found that AI was most effective at shifting opinions on topics that people didnโt already have strong views on. This suggests that AI can exploit the undecided middle by providing personalised persuasion. Unlike your annoying uncle at Thanksgiving, AIโs debate style is analytical and structured, making points that feel crafted specifically for the individual.
๐ t.me/techpsyche
New research reveals that AI can be just as persuasive as humans in debates, and even more so when armed with information about a personโs age, gender, ethnicity, and political views. Francesco Salvi, a researcher at the Swiss Federal Institute of Technology, warns that if persuasive AI can be deployed at scale, it could lead to armies of bots microtargeting undecided voters with tailored political narratives that feel authentic.
The study, which involved 600 debates, found that AI was most effective at shifting opinions on topics that people didnโt already have strong views on. This suggests that AI can exploit the undecided middle by providing personalised persuasion. Unlike your annoying uncle at Thanksgiving, AIโs debate style is analytical and structured, making points that feel crafted specifically for the individual.
๐ t.me/techpsyche
Remote Phala Network Ambassador Job at Phala Network
- Good for someone who is into Web 3 & decentralized Technologies
Apply Here:
https://kenyatrends.co.ke/gh38
Global Tech Jobs Here๐
https://t.me/techpsyche
SHARE WITH YOUR FRIENDS๐ฅณ๐ฅณ
- Good for someone who is into Web 3 & decentralized Technologies
Apply Here:
https://kenyatrends.co.ke/gh38
Global Tech Jobs Here๐
https://t.me/techpsyche
SHARE WITH YOUR FRIENDS๐ฅณ๐ฅณ
Preparing for a data science interview can be challenging, but with the right approach, you can increase your chances of success. Here are some tips to help you prepare for your next data science interview:
๐ 1. Review the Fundamentals: Make sure you have a thorough understanding of the fundamentals of statistics, probability, and linear algebra. You should also be familiar with data structures, algorithms, and programming languages like Python, R, and SQL.
๐ 2. Brush up on Machine Learning: Machine learning is a key aspect of data science. Make sure you have a solid understanding of different types of machine learning algorithms like supervised, unsupervised, and reinforcement learning.
๐ 3. Practice Coding: Practice coding questions related to data structures, algorithms, and data science problems. You can use online resources like HackerRank, LeetCode, and Kaggle to practice.
๐ 4. Build a Portfolio: Create a portfolio of projects that demonstrate your data science skills. This can include data cleaning, data wrangling, exploratory data analysis, and machine learning projects.
๐ 5. Practice Communication: Data scientists are expected to effectively communicate complex technical concepts to non-technical stakeholders. Practice explaining your projects and technical concepts in simple terms.
๐ 6. Research the Company: Research the company you are interviewing with and their industry. Understand how they use data and what data science problems they are trying to solve.
Learn DatA & AI: https://365datascience.pxf.io/Z6KDgk
Free Notes & Books to learn Data Science: https://t.me/datascienceresourcestp
Python Project Ideas: https://t.me/pythonresourcestp/74
Best Resources to learn Data Science ๐๐
Python Tutorial (http://pythontutorial.net/)
Data Science Course (http://kaggle.com/learn) by Kaggle
Machine Learning Course (http://developers.google.com/machine-learning/crash-course) by Google
Best Data Science & Machine Learning Resources (https://topmate.io/learning_resources/1406977)
Interview Process for Data Science Role at Amazon (https://t.me/datascienceresourcestp/85)
Python Interview Resources (https://t.me/pythonresourcestp/40)
Join for more free courses
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ENJOY LEARNING๐๐
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๐ 1. Review the Fundamentals: Make sure you have a thorough understanding of the fundamentals of statistics, probability, and linear algebra. You should also be familiar with data structures, algorithms, and programming languages like Python, R, and SQL.
๐ 2. Brush up on Machine Learning: Machine learning is a key aspect of data science. Make sure you have a solid understanding of different types of machine learning algorithms like supervised, unsupervised, and reinforcement learning.
๐ 3. Practice Coding: Practice coding questions related to data structures, algorithms, and data science problems. You can use online resources like HackerRank, LeetCode, and Kaggle to practice.
๐ 4. Build a Portfolio: Create a portfolio of projects that demonstrate your data science skills. This can include data cleaning, data wrangling, exploratory data analysis, and machine learning projects.
๐ 5. Practice Communication: Data scientists are expected to effectively communicate complex technical concepts to non-technical stakeholders. Practice explaining your projects and technical concepts in simple terms.
๐ 6. Research the Company: Research the company you are interviewing with and their industry. Understand how they use data and what data science problems they are trying to solve.
Learn DatA & AI: https://365datascience.pxf.io/Z6KDgk
Free Notes & Books to learn Data Science: https://t.me/datascienceresourcestp
Python Project Ideas: https://t.me/pythonresourcestp/74
Best Resources to learn Data Science ๐๐
Python Tutorial (http://pythontutorial.net/)
Data Science Course (http://kaggle.com/learn) by Kaggle
Machine Learning Course (http://developers.google.com/machine-learning/crash-course) by Google
Best Data Science & Machine Learning Resources (https://topmate.io/learning_resources/1406977)
Interview Process for Data Science Role at Amazon (https://t.me/datascienceresourcestp/85)
Python Interview Resources (https://t.me/pythonresourcestp/40)
Join for more free courses
https://t.me/techpsyche
Like for more โค๏ธ
ENJOY LEARNING๐๐
Join Our WhatsApp Channel:
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
OpenAI acquired io, the AI device startup co-founded by Jony Ive
Jony Ive was the designer of Iphone.
๐ t.me/techpsyche
Jony Ive was the designer of Iphone.
๐ t.me/techpsyche
Forwarded from Mobile Dev Resources . Android . iOS . Flutter . Kotlin . Swift . Java . React Native
Flutter vs. React Native A Comprehensive Comparison
When it comes to cross-platform mobile app development, two of the most popular frameworks are Flutter and React Native. Both have their unique strengths and can be the right choice depending on your project needs.
1. Overview
- Flutter: Developed by Google, Flutter is an open-source UI toolkit that allows developers to create natively compiled applications for mobile, web, and desktop from a single codebase. It uses the Dart programming language.
- React Native: Developed by Facebook, React Native is a popular framework for building mobile applications using JavaScript and React. It enables developers to create apps for both iOS and Android with a single codebase.
2. Performance
- Flutter: Known for its high performance, Flutter uses Dart's ahead-of-time (AOT) compilation to compile the code into native machine code, which results in faster execution and smoother performance.
- React Native: While React Native also offers good performance, it relies on JavaScript to bridge the gap between the app and the native components, which can sometimes lead to performance bottlenecks.
Optimize your App's Perfomance: t.me/mobiledevresourcestp/86
3. Development Experience
- Flutter: Flutter provides a rich set of pre-designed widgets and a hot reload feature, which allows developers to see changes in real-time without restarting the app. However, Dart is less commonly used compared to JavaScript, which might require a learning curve.
- React Native: React Native benefits from the vast ecosystem of JavaScript and React. It also supports hot reloading, making the development process faster and more efficient. The familiarity of JavaScript can be a significant advantage for many developers
4. Community and Ecosystem
- Flutter: Flutter has a growing community and is backed by Google, which ensures regular updates and improvements. The ecosystem is expanding, but it is still not as extensive as React Native's.
- React Native: With a larger and more mature community, React Native has a wealth of libraries, tools, and resources available. This extensive ecosystem can be very beneficial for developers looking for third-party integrations.
5. Use Cases
- Flutter: Ideal for projects that require a high level of custom UI and performance, such as gaming apps or applications with complex animations.
- React Native: Best suited for applications that need to be developed quickly and efficiently, especially if the development team is already familiar with JavaScript and React.
Conclusion
- Both Flutter and React Native are powerful frameworks for cross-platform app development. Your choice between the two should depend on your specific project requirements, team expertise, and performance needs. Flutter excels in performance and custom UI, while React Native offers a more extensive ecosystem and faster development with JavaScript.
Flutter Roadmap Here: https://t.me/mobiledevresourcestp/84
Why you should use React Native in 2025: https://t.me/mobiledevresourcestp/94
Join Our WhatsApp Channel:
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R
When it comes to cross-platform mobile app development, two of the most popular frameworks are Flutter and React Native. Both have their unique strengths and can be the right choice depending on your project needs.
1. Overview
- Flutter: Developed by Google, Flutter is an open-source UI toolkit that allows developers to create natively compiled applications for mobile, web, and desktop from a single codebase. It uses the Dart programming language.
- React Native: Developed by Facebook, React Native is a popular framework for building mobile applications using JavaScript and React. It enables developers to create apps for both iOS and Android with a single codebase.
2. Performance
- Flutter: Known for its high performance, Flutter uses Dart's ahead-of-time (AOT) compilation to compile the code into native machine code, which results in faster execution and smoother performance.
- React Native: While React Native also offers good performance, it relies on JavaScript to bridge the gap between the app and the native components, which can sometimes lead to performance bottlenecks.
Optimize your App's Perfomance: t.me/mobiledevresourcestp/86
3. Development Experience
- Flutter: Flutter provides a rich set of pre-designed widgets and a hot reload feature, which allows developers to see changes in real-time without restarting the app. However, Dart is less commonly used compared to JavaScript, which might require a learning curve.
- React Native: React Native benefits from the vast ecosystem of JavaScript and React. It also supports hot reloading, making the development process faster and more efficient. The familiarity of JavaScript can be a significant advantage for many developers
4. Community and Ecosystem
- Flutter: Flutter has a growing community and is backed by Google, which ensures regular updates and improvements. The ecosystem is expanding, but it is still not as extensive as React Native's.
- React Native: With a larger and more mature community, React Native has a wealth of libraries, tools, and resources available. This extensive ecosystem can be very beneficial for developers looking for third-party integrations.
5. Use Cases
- Flutter: Ideal for projects that require a high level of custom UI and performance, such as gaming apps or applications with complex animations.
- React Native: Best suited for applications that need to be developed quickly and efficiently, especially if the development team is already familiar with JavaScript and React.
Conclusion
- Both Flutter and React Native are powerful frameworks for cross-platform app development. Your choice between the two should depend on your specific project requirements, team expertise, and performance needs. Flutter excels in performance and custom UI, while React Native offers a more extensive ecosystem and faster development with JavaScript.
Flutter Roadmap Here: https://t.me/mobiledevresourcestp/84
Why you should use React Native in 2025: https://t.me/mobiledevresourcestp/94
Join Our WhatsApp Channel:
https://whatsapp.com/channel/0029VahGttK5a24AXAJDjm2R