MLXIO
stock market candlestick chart on dark screen
TradingMay 19, 2026· 11 min read· By Priya Dasgupta

Master Technical Analysis Software to Crush Stock Trading

Share
Updated on May 19, 2026

Choosing to use technical analysis software can be a game-changer for improving your stock trading decisions. With the right setup and approach, traders can leverage powerful tools and indicators to analyze price movements, backtest strategies, and automate their trading—all of which are essential for navigating today’s financial markets. In this comprehensive tutorial, we’ll walk you through every step of the process, from installation to advanced use cases, using real-world data, platform examples, and actionable techniques.

The Role of Technical Analysis Software in Trading

Understanding how to use technical analysis software is crucial for traders who want to make informed decisions based on price patterns, trends, and statistical signals. Unlike manual charting or basic web tools, dedicated platforms such as MetaTrader 5 provide a suite of advanced features designed for in-depth analysis.

“MetaTrader 5 offers all the essentials for technical analysis: indicators, analytical objects, and unlimited charts. These tools are further supported by a wide range of add-ons, and its MQL programming language allows you to build custom indicators.”
— newtrading.io

The key benefits of technical analysis software include:

  • Comprehensive Charting: Visualize market data with customizable charts.
  • Access to Technical Indicators: Apply built-in or custom indicators for deeper insights.
  • Automation: Develop and run algorithmic trading strategies.
  • Signal Services: Copy or subscribe to other traders’ signals.
  • Backtesting: Test strategies on historical data to assess their viability.

This step-by-step guide will focus on using MetaTrader 5 as the primary example, given its feature-rich environment and widespread adoption in 2026.

Setting Up Your Technical Analysis Software

Getting started with technical analysis software requires proper installation, configuration, and an understanding of basic requirements.

Downloading and Installing MetaTrader 5

MetaTrader 5 is available for free on web, mobile, and desktop platforms. The installation process is straightforward:

  1. Download the Platform: Visit the official MetaTrader 5 website or your broker’s portal to download the application for your operating system.
  2. Install the Application: Follow on-screen instructions to complete the installation.
  3. Create or Connect a Broker Account: To start trading or using live data, you must connect MetaTrader 5 to a supported brokerage account.

Minimum System Requirements

MetaTrader 5 is lightweight and does not require high-end hardware. However, ensure your device meets the following:

  • Operating System: Windows, macOS, Linux (via Wine), Android, or iOS
  • Internet Connection: Stable broadband
  • RAM: At least 2GB recommended for smooth operation

“Please ensure your container has the necessary resources allocated to it. We recommend 2GiB of memory allocated to accommodate the application server.”
— hub.docker.com

While this recommendation comes from a different software context, the principle applies: allocate enough resources for smooth performance.

Initial Configuration

After installation:

  • Set Up Data Sources: Connect your broker account to access market data.
  • Customize Layout: Arrange charts, toolbars, and windows to your workflow.
  • Install Add-Ons or Custom Indicators: MetaTrader 5 supports a variety of add-ons and the MQL language for custom scripts.
Platform Supported Markets Indicator Support Automation Cost
MetaTrader 5 Forex, Stocks, Futures Yes (built-in & custom via MQL) Yes Free

Understanding Key Technical Indicators and How to Apply Them

Technical indicators are the backbone of any analysis strategy. MetaTrader 5 comes with a rich library of built-in indicators, and the ability to create your own.

  • Moving Averages (MA): Smooth out price data to identify trends.
  • Relative Strength Index (RSI): Measures the speed and change of price movements.
  • MACD (Moving Average Convergence Divergence): Follows trend and momentum.
  • Bollinger Bands: Shows volatility and potential overbought/oversold conditions.

Applying an indicator in MetaTrader 5 is simple:

  1. Open a Chart: Select the asset you wish to analyze.
  2. Insert Indicator: Navigate to the 'Insert' menu, choose 'Indicators', and pick from the built-in list.
  3. Configure Parameters: Adjust the settings (periods, colors, etc.) to fit your strategy.
  4. Visualize on Chart: The indicator is overlaid on your selected price chart.

“MetaTrader 5 offers all the essentials for technical analysis: indicators, analytical objects, and unlimited charts.”
— newtrading.io

Custom Indicators

If the default tools aren’t enough, use the MQL language to code your own. This flexibility allows you to implement proprietary algorithms or combine several metrics for unique signals.

# Example: Simple Moving Average in MQL (MetaTrader 5 pseudocode)
double sma(int period, double price[]) {
    double sum = 0;
    for(int i=0; i<period; i++) {
        sum += price[i];
    }
    return sum / period;
}

Chart Patterns and Trend Analysis Techniques

Recognizing patterns and trends is essential for making trading decisions. Technical analysis software like MetaTrader 5 provides various tools to assist in this process.

Common Chart Patterns

  • Head and Shoulders: Indicates potential trend reversal.
  • Double Top/Bottom: Signals possible trend reversal points.
  • Triangles (Ascending, Descending, Symmetrical): Suggests continuation or breakout.

Trend Analysis Tools in MetaTrader 5

  • Trendlines: Drawn manually or using analytical objects to identify support/resistance.
  • Channels: Parallel lines to visualize price movement ranges.
  • Unlimited Charts: Analyze multiple timeframes and assets simultaneously.
Feature MetaTrader 5 Support
Trendlines Yes
Channels Yes
Pattern Drawing Yes (manual/objects)

“Despite its somewhat outdated interface, MetaTrader 5 offers all the essentials for technical analysis: indicators, analytical objects, and unlimited charts.”
— newtrading.io

Using Alerts and Automated Signals to Time Trades

A major advantage when you use technical analysis software is the ability to automate parts of your trading.

Setting Alerts

MetaTrader 5 allows you to set alerts based on price levels, indicator values, or even custom scripts. Alerts can notify you via sound, email, or push notifications, ensuring you never miss a trading opportunity.

  • Price Alerts: Trigger when a security hits a specified price.
  • Indicator Alerts: Fire when an indicator crosses a threshold (e.g., RSI over 70).
  • Custom Alerts: Use the MQL language to create complex conditions.

Automated Signals and Copy Trading

MetaTrader 5 users can subscribe to signal services, enabling automatic copying of trades from other traders.

“You can subscribe to a signal service that lets you automatically copy trades from other traders.”
— newtrading.io

This is especially helpful for beginners or those who want to diversify their strategies.

Automation Type MetaTrader 5 Support
Price Alerts Yes
Indicator Alerts Yes
Signal Subscription Yes
Automated Trading Yes (full MQL support)

Backtesting Strategies with Historical Data

One of the most powerful features when you use technical analysis software is the ability to backtest your strategies. This means running your trading logic against historical data to see how it would have performed.

Backtesting in MetaTrader 5

  • Built-In Backtesting Engine: Run algorithmic strategies on past price data.
  • Visualization: See trades plotted on historical charts.
  • Optimization: Tweak parameters and rerun tests to find the best-performing settings.

“The platform is also widely recognized for its algorithmic trading capabilities, offering users the ability to create and run automated trading systems.”
— newtrading.io

Why Backtesting Matters

  • Validate Strategies: Avoid relying on untested ideas.
  • Understand Risk/Reward: Evaluate drawdown, win rates, and expected returns.
  • Refine Approaches: Optimize parameters before risking real capital.

Integrating Technical Analysis with Fundamental Insights

While technical analysis focuses on price action, combining it with fundamental analysis can provide a more holistic view of the markets.

Practical Integration

MetaTrader 5 is primarily a technical platform; at the time of writing, direct integration with fundamental data (such as earnings, news feeds, or analyst ratings) is not a core feature. However, traders often:

  • Monitor Economic Calendars: Many brokers provide news feeds and calendars within MetaTrader 5.
  • Overlay Technical Signals: Use technical indicators to confirm or reject trade ideas based on fundamentals.

“Combining news articles about similar events” and “Predicting stock market trends” are listed as relevant deep learning project ideas, highlighting the value of integrating different data sources for better decisions.
— MIT Deep Learning Course

Advanced Integration

For those with programming skills, it’s possible to use the MQL language to fetch and incorporate external data, or use APIs to blend technical and fundamental insights.

Common Mistakes to Avoid When Using Technical Software

Even the best software cannot compensate for poor practices. Here are common mistakes to watch for:

  1. Over-Reliance on Indicators: More is not always better. Too many conflicting signals can confuse rather than clarify.
  2. Ignoring Backtesting: Trading untested strategies can lead to major losses.
  3. Neglecting Market Context: Technical signals work best when aligned with broader market conditions.
  4. Failure to Update Software: Outdated platforms may have bugs or lack essential features.
  5. Poor Resource Allocation: Inadequate system resources can cause software crashes or lag.

“Most modern browsers tend to install updates automatically… You can usually check for updates on the browser 'About' page.”
— MDN Web Docs

Although this advice is about web browsers, the principle applies: keep your technical analysis software up to date for best performance and security.

Case Study: Applying Technical Analysis to a Real Trade

Let’s walk through a practical example using MetaTrader 5.

Scenario

Suppose you want to trade a popular stock based on a moving average crossover strategy.

Step-by-Step Process

  1. Open MetaTrader 5 and load the stock’s chart.
  2. Apply Two Moving Averages:
    • Fast MA (e.g., 10 periods)
    • Slow MA (e.g., 50 periods)
  3. Set Alerts for when the fast MA crosses above/below the slow MA.
  4. Backtest the strategy using historical data to review past performance.
  5. Automate the strategy using MetaTrader 5’s MQL language for real-time signal generation or even auto-trading.
# MQL pseudo-code for crossover alert
if (FastMA > SlowMA) and (PrevFastMA <= PrevSlowMA) {
    Alert("Bullish crossover: Consider going long");
}
  1. Monitor the Trade: Use the alert or automated execution. Track the outcome and refine parameters as needed.

“Run algorithmic strategies on past price data… The platform is also widely recognized for its algorithmic trading capabilities.”
— newtrading.io

FAQ

Q1: What is the best technical analysis software for beginners in 2026?
A: According to newtrading.io, MetaTrader 5 is widely recognized for its comprehensive feature set, including unlimited charts, built-in and custom indicators, and automation capabilities. It is available for free on web, mobile, and desktop.

Q2: Does MetaTrader 5 support automated trading?
A: Yes. MetaTrader 5 supports full algorithmic trading through its MQL programming language, allowing users to create and run automated trading systems.

Q3: Can I use technical analysis software for both forex and stock trading?
A: MetaTrader 5 supports forex, stocks, and futures markets, making it versatile for different asset classes.

Q4: How do I backtest a trading strategy in MetaTrader 5?
A: MetaTrader 5 has a built-in backtesting engine. You can test your strategy against historical price data, visualize results, and optimize parameters.

Q5: Are there any costs associated with MetaTrader 5?
A: MetaTrader 5 is available for free. However, you need to connect to a supported broker account to access live trading and market data.

Q6: Can I create custom indicators in MetaTrader 5?
A: Yes. The platform’s MQL language allows you to develop custom indicators and scripts.

Bottom Line

When you use technical analysis software such as MetaTrader 5, you gain access to a suite of advanced tools that can significantly enhance your trading decisions. The platform provides unlimited charts, built-in and custom indicators, robust backtesting, and powerful automation features—all for free. However, success depends on your discipline: always backtest strategies, avoid overcomplicating your analysis, and keep your software updated. Integrating technical analysis with a broader understanding of market context and, where possible, fundamental insights will further improve your results. By following the steps and best practices outlined here, you’ll be well on your way to making more consistent, data-driven trading decisions in 2026 and beyond.

Sources & References

Content sourced and verified on May 19, 2026

  1. 1
    4 Best Technical Analysis Tools For Traders (2026)

    https://www.newtrading.io/technical-analysis-tools-software/

  2. 2
    atlassian/jira-software - Docker Image

    https://hub.docker.com/r/atlassian/jira-software

  3. 3
    GitHub - abusufyanvu/6S191_MIT_DeepLearning: MIT Introduction to Deep Learning (6.S191) Instructors: Alexander Amini and Ava Soleimany Course Information Summary Prerequisites Schedule Lectures Labs, Final Projects, Grading, and Prizes Software labs Gather.Town lab + Office Hour sessions Final project Paper Review Project Proposal Presentation Project Proposal Grading Rubric Past Project Proposal Ideas Awards + Categories Important Links and Emails Course Information Summary MIT's introductory course on deep learning methods with applications to computer vision, natural language processing, biology, and more! Students will gain foundational knowledge of deep learning algorithms and get practical experience in building neural networks in TensorFlow. Course concludes with a project proposal competition with feedback from staff and a panel of industry sponsors. Prerequisites We expect basic knowledge of calculus (e.g., taking derivatives), linear algebra (e.g., matrix multiplication), and probability (e.g., Bayes theorem) -- we'll try to explain everything else along the way! Experience in Python is helpful but not necessary. This class is taught during MIT's IAP term by current MIT PhD researchers. Listeners are welcome! Schedule Monday Jan 18, 2021 Lecture: Introduction to Deep Learning and NNs Lab: Lab 1A Tensorflow and building NNs from scratch Tuesday Jan 19, 2021 Lecture: Deep Sequence Modelling Lab: Lab 1B Music Generation using RNNs Wednesday Jan 20, 2021 Lecture: Deep Computer Vision Lab: Lab 2A Image classification and detection Thursday Jan 21, 2021 Lecture: Deep Generative Modelling Lab: Lab 2B Debiasing facial recognition systems Friday Jan 22, 2021 Lecture: Deep Reinforcement Learning Lab: Lab 3 pixel-to-control planning Monday Jan 25, 2021 Lecture: Limitations and New Frontiers Lab: Lab 3 continued Tuesday Jan 26, 2021 Lecture (part 1): Evidential Deep Learning Lecture (part 2): Bias and Fairness Lab: Work on final assignments Lab competition entries due at 11:59pm ET on Canvas! Lab 1, Lab 2, and Lab 3 Wednesday Jan 27, 2021 Lecture (part 1): Nigel Duffy, Ernst & Young Lecture (part 2): Kate Saenko, Boston University and MIT-IBM Watson AI Lab Lab: Work on final assignments Assignments due: Sign up for Final Project Competition Thursday Jan 28, 2021 Lecture (part 1): Sanja Fidler, U. Toronto, Vector Institute, and NVIDIA Lecture (part 2): Katherine Chou, Google Lab: Work on final assignments Assignments due: 1 page paper review (if applicable) Friday Jan 29, 2021 Lecture: Student project pitch competition Lab: Awards ceremony and prize giveaway Assignments due: Project proposals (if applicable) Lectures Lectures will be held starting at 1:00pm ET from Jan 18 - Jan 29 2021, Monday through Friday, virtually through Zoom. Current MIT students, faculty, postdocs, researchers, staff, etc. will be able to access the lectures during this two week period, synchronously or asynchronously, via the MIT Canvas course webpage (MIT internal only). Lecture recordings will be uploaded to the Canvas as soon as possible; students are not required to attend any lectures synchronously. Please see the Canvas for details on Zoom links. The public edition of the course will only be made available after completion of the MIT course. Labs, Final Projects, Grading, and Prizes Course will be graded during MIT IAP for 6 units under P/D/F grading. Receiving a passing grade requires completion of each software lab project (through honor code, with submission required to enter lab competitions), a final project proposal/presentation or written review of a deep learning paper (submission required), and attendance/lecture viewing (through honor code). Submission of a written report or presentation of a project proposal will ensure a passing grade. MIT students will be eligible for prizes and awards as part of the class competitions. There will be two parts to the competitions: (1) software labs and (2) final projects. More information is provided below. Winners will be announced on the last day of class, with thousands of dollars of prizes being given away! Software labs There are three TensorFlow software lab exercises for the course, designed as iPython notebooks hosted in Google Colab. Software labs can be found on GitHub: https://github.com/aamini/introtodeeplearning. These are self-paced exercises and are designed to help you gain practical experience implementing neural networks in TensorFlow. For registered MIT students, submission of lab materials is not necessary to get credit for the course or to pass the course. At the end of each software lab there will be task-associated materials to submit (along with instructions) for entry into the competitions, open to MIT students and affiliates during the IAP offering. This includes MIT students/affiliates who are taking the class as listeners -- you are eligible! These instructions are provided at the end of each of the labs. Completing these tasks and submitting your materials to Canvas will enter you into a per-lab competition. MIT students and affiliates will be eligible for prizes during the IAP offering; at the end of the course, prize-winners will be awarded with their prizes. All competition submissions are due on January 26 at 11:59pm ET to Canvas. For the software lab competitions, submissions will be judged on the basis of the following criteria: Strength and quality of final results (lab dependent) Soundness of implementation and approach Thoroughness and quality of provided descriptions and figures Gather.Town lab + Office Hour sessions After each day’s lecture, there will be open Office Hours in the class GatherTown, up until 3pm ET. An MIT email is required to log in and join the GatherTown. During these sessions, there will not be a walk through or dictation of the labs; the labs are designed to be self-paced and to be worked on on your own time. The GatherTown sessions will be hosted by course staff and are held so you can: Ask questions on course lectures, labs, logistics, project, or anything else; Work on the labs in the presence of classmates/TAs/instructors; Meet classmates to find groups for the final project; Group work time for the final project; Bring the class community together. Final project To satisfy the final project requirement for this course, students will have two options: (1) write a 1 page paper review (single-spaced) on a recent deep learning paper of your choice or (2) participate and present in the project proposal pitch competition. The 1 page paper review option is straightforward, we propose some papers within this document to help you get started, and you can satisfy a passing grade with this option -- you will not be eligible for the grand prizes. On the other hand, participation in the project proposal pitch competition will equivalently satisfy your course requirements but additionally make you eligible for the grand prizes. See the section below for more details and requirements for each of these options. Paper Review Students may satisfy the final project requirement by reading and reviewing a recent deep learning paper of their choosing. In the written review, students should provide both: 1) a description of the problem, technical approach, and results of the paper; 2) critical analysis and exposition of the limitations of the work and opportunities for future work. Reviews should be submitted on Canvas by Thursday Jan 28, 2021, 11:59:59pm Eastern Time (ET). Just a few paper options to consider... https://papers.nips.cc/paper/2017/file/3f5ee243547dee91fbd053c1c4a845aa-Paper.pdf https://papers.nips.cc/paper/2018/file/69386f6bb1dfed68692a24c8686939b9-Paper.pdf https://papers.nips.cc/paper/2020/file/1457c0d6bfcb4967418bfb8ac142f64a-Paper.pdf https://science.sciencemag.org/content/362/6419/1140 https://papers.nips.cc/paper/2018/file/0e64a7b00c83e3d22ce6b3acf2c582b6-Paper.pdf https://arxiv.org/pdf/1906.11829.pdf https://www.nature.com/articles/s42256-020-00237-3 https://pubmed.ncbi.nlm.nih.gov/32084340/ Project Proposal Presentation Keyword: proposal This is a 2 week course so we do not require results or working implementations! However, to win the top prizes, nice, clear results and implementations will demonstrate feasibility of your proposal which is something we look for! Logistics -- please read! You must sign up to present before 11:59:59pm Eastern Time (ET) on Wednesday Jan 27, 2021 Slides must be in a Google Slide before 11:59:59pm Eastern Time (ET) on Thursday Jan 28, 2021 Project groups can be between 1 and 5 people Listeners welcome To be eligible for a prize you must have at least 1 registered MIT student in your group Each participant will only be allowed to be in one group and present one project pitch Synchronous attendance on 1/29/21 is required to make the project pitch! 3 min presentation on your idea (we will be very strict with the time limits) Prizes! (see below) Sign up to Present here: by 11:59pm ET on Wednesday Jan 27 Once you sign up, make your slide in the following Google Slides; submit by midnight on Thursday Jan 28. Please specify the project group # on your slides!!! Things to Consider This doesn’t have to be a new deep learning method. It can just be an interesting application that you apply some existing deep learning method to. What problem are you solving? Are there use cases/applications? Why do you think deep learning methods might be suited to this task? How have people done it before? Is it a new task? If so, what are similar tasks that people have worked on? In what aspects have they succeeded or failed? What is your method of solving this problem? What type of model + architecture would you use? Why? What is the data for this task? Do you need to make a dataset or is there one publicly available? What are the characteristics of the data? Is it sparse, messy, imbalanced? How would you deal with that? Project Proposal Grading Rubric Project proposals will be evaluated by a panel of judges on the basis of the following three criteria: 1) novelty and impact; 2) technical soundness, feasibility, and organization, including quality of any presented results; 3) clarity and presentation. Each judge will award a score from 1 (lowest) to 5 (highest) for each of the criteria; the average score from each judge across these criteria will then be averaged with that of the other judges to provide the final score. The proposals with the highest final scores will be selected for prizes. Here are the guidelines for the criteria: Novelty and impact: encompasses the potential impact of the project idea, its novelty with respect to existing approaches. Why does the proposed work matter? What problem(s) does it solve? Why are these problems important? Technical soundness, feasibility, and organization: encompasses all technical aspects of the proposal. Do the proposed methodology and architecture make sense? Is the architecture the best suited for the proposed problem? Is deep learning the best approach for the problem? How realistic is it to implement the idea? Was there any implementation of the method? If results and data are presented, we will evaluate the strength of the results/data. Clarity and presentation: encompasses the delivery and quality of the presentation itself. Is the talk well organized? Are the slides aesthetically compelling? Is there a clear, well-delivered narrative? Are the problem and proposed method clearly presented? Past Project Proposal Ideas Recipe Generation with RNNs Can we compress videos with CNN + RNN? Music Generation with RNNs Style Transfer Applied to X GAN’s on a new modality Summarizing text/news articles Combining news articles about similar events Code or spec generation Multimodal speech → handwriting Generate handwriting based on keywords (i.e. cursive, slanted, neat) Predicting stock market trends Show language learners articles or videos at their level Transfer of writing style Chemical Synthesis with Recurrent Neural networks Transfer learning to learn something in a domain for which it’s hard or risky to gather data or do training RNNs to model some type of time series data Computer vision to coach sports players Computer vision system for safety brakes or warnings Use IBM Watson API to get the sentiment of your Facebook newsfeed Deep learning webcam to give wifi-access to friends or improve video chat in some way Domain-specific chatbot to help you perform a specific task Detect whether a signature is fraudulent Awards + Categories Final Project Awards: 1x NVIDIA RTX 3080 4x Google Home Max 3x Display Monitors Software Lab Awards: Bose headphones (Lab 1) Display monitor (Lab 2) Bebop drone (Lab 3) Important Links and Emails Course website: http://introtodeeplearning.com Course staff: [email protected] Piazza forum (MIT only): https://piazza.com/mit/spring2021/6s191 Canvas (MIT only): https://canvas.mit.edu/courses/8291 Software lab repository: https://github.com/aamini/introtodeeplearning Lab/office hour sessions (MIT only): https://gather.town/app/56toTnlBrsKCyFgj/MITDeepLearning

    https://github.com/abusufyanvu/6S191_MIT_DeepLearning

  4. 4
    Installing basic software - Learn web development | MDN

    https://developer.mozilla.org/en-US/docs/Learn_web_development/Getting_started/Environment_setup/Installing_software

PD

Written by

Priya Dasgupta

Finance & Markets Correspondent

Priya tracks global financial markets, central bank policy, and macroeconomic signals. She specializes in making complex market data accessible to everyday investors and business decision-makers.

Stock MarketsEconomic PolicyCentral BanksETFsMarket Analysis

Explore More Topics

TechnologyAI / MLTradingFinanceCryptoStartupsCybersecurityCreatorsScienceBusinessGlobal Trends

Related Articles

a screen shot of a stock chart on a computer screen
TradingMay 19, 2026

7 Must-Have Features in Technical Analysis Software for Traders

Choosing technical analysis software with key features like advanced charting and vast indicator libraries can transform your stock trading results.

9 min read

Hands holding smartphone showing stock market data
TradingMay 19, 2026

Advanced Trading Platforms Reveal Hidden Technical Analysis Power

Advanced trading platforms with built-in technical analysis tools give traders faster, more accurate market insights to boost strategic decisions.

9 min read

stock market candlestick chart on dark screen
TradingMay 19, 2026

7 Stock Trading Platforms Crushing Technical Analysis in 2026

Discover the 7 best stock trading platforms that dominate technical analysis in 2026 with advanced tools and real-time data.

11 min read

Stock market chart shows a downward trend.
TradingMay 13, 2026

2026’s Charting Tools That Crush Stock Trading Risks

Choosing the right charting tools in 2026 is crucial for trading success. This guide reveals key features to match your style and budget.

11 min read

Stock charts are displayed on multiple screens.
TradingMay 13, 2026

Top 5 Technical Analysis Software Crushing Day Trading in 2026

Discover the top technical analysis software that gives day traders real-time speed, customization, and automation edge in 2026.

7 min read

Modern laptop displaying a vibrant landscape on screen.
TechnologyMay 20, 2026

Lenovo Shocks Gaming World with Dimensity 9500S Tablet Launch

Lenovo’s Legion Y900 2026 drops a surprising sub-flagship Dimensity 9500S chip, balancing cost and gaming power in a new tablet.

3 min read

man in blue dress shirt wearing blue framed eyeglasses
TechnologyMay 20, 2026

Samsung and Google Spark AI Smart Glasses Revolution at I/O 2026

Samsung and Google unveil stylish AI-powered smart glasses at Google I/O 2026, aiming to redefine wearable tech with hands-free AI-driven experiences.

5 min read

Hand holding a smartphone with colorful app icons.
TechnologyMay 20, 2026

Itel A100 Pro goes official with a 6.6-inch display and a 5,

Itel’s A100 Pro offers a large 6.6-inch 90Hz display and a 5,000mAh battery, delivering endurance and smooth visuals for budget buyers in India.

4 min read

black and white nike logo
CreatorsMay 20, 2026

Apple TV Sparks Buzz with Thriller-Comedy Maximum Pleasure Guaranteed

Apple TV launches Maximum Pleasure Guaranteed, a bold thriller-comedy blending suspense and dark humor with two episodes out now.

4 min read

a laptop on a table
CryptoMay 20, 2026

Warren Declares Coinbase, Ripple Crypto Bank Charters Illegal

Elizabeth Warren challenges OCC’s crypto bank charters for Coinbase and Ripple as illegal, risking a major regulatory upheaval in crypto banking.

5 min read