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Dive into the hottest AI breakthroughs of the week—handpicked just for you!
Super Important AI News 🔥 🔥 🔥
Featured AI Update 🛡️🛡️🛡️
Microsoft AI has recently introduced Phi-4-multimodal and Phi-4-mini, the newest additions to its Phi family of SLMs. These models have been developed with a clear focus on streamlining multimodal processing. Phi-4-multimodal is designed to handle text, speech, and visual inputs concurrently, all within a unified architecture. This integrated approach means that a single model can now interpret and generate responses based on varied data types without the need for separate, specialized systems.
Phi-4-mini, with its 3.8-billion parameters, is built as a dense, decoder-only transformer. It features grouped-query attention and boasts a vocabulary of 200,000 tokens, enabling it to handle sequences of up to 128,000 tokens. Despite its smaller size, Phi-4-mini performs remarkably well in tasks that require deep reasoning and language understanding. One of its standout features is the capability for function calling—allowing it to interact with external tools and APIs, thus extending its practical utility without requiring a larger, more resource-intensive model…..
Coding Tutorial 🎖️🎖️🎖️
In this tutorial, we will build an interactive web scraping project in Google Colab! This guide will walk you through extracting live weather forecast data from the U.S. National Weather Service. You’ll learn to set up your environment, write a Python script using BeautifulSoup and requests, and integrate an interactive UI with ipywidgets. This tutorial provides a step-by-step approach to collecting, displaying, and saving weather data, all within a single, self-contained Colab notebook.
import requests
from bs4 import BeautifulSoup
import csv
from google.colab import files
import ipywidgets as widgets
from IPython.display import display, clear_output, FileLink
import pandas as pd
