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Holiday shopping is stressful for everybody… but when you’re blind, it hits different.
Checkout lines twisting everywhere, carts blocking the aisles, people saying “over there” like that’s a real direction — it gets wild out here. And somehow, people still go silent when you’re about to bump into them.
I made a whole video about what it’s really like during the holidays. If you want to understand what we go through (and maybe laugh a little), watch it here 👇Click here
Today I checked out an app that honestly surprised me. It’s called Scribe Me, and it’s built from the ground up for visually impaired folks — PDF reading, PowerPoints, image descriptions, Live Assist… all in one place.
I tried it on real files, and the results were way better than I expected. Even with my voice still sounding a little raspy, this was worth filming.
If you want to see how it works and why it could become one of the best AI tools for blind users, check out the video here 👇Scribe Me App Review: The Best AI Scanner & Live Assist Tool for the Blind?
FARA-7B, a compact computer-use model that’s powerful enough to run locally without burning your machine to the ground. This thing isn’t another bloated agent chained to the cloud. It’s built to run on regular hardware and still handle real tasks.
What makes it stand out is its simplicity. Most agents use a giant stack of subsystems that click, scroll, guess at the screen, and call multiple helper models behind the scenes. FARA-7B does the opposite. It looks directly at a screenshot and decides what to do next. No scaffolding. No accessibility-tree parsing. No five-model circus happening backstage. Just one model handling everything.
The magic comes from Microsoft’s synthetic data engine, Faragen. Instead of harvesting human browsing logs, they trained the model with AIs performing tasks across more than 70,000 websites. These weren’t perfect robotic demos either—they included mistakes, retries, scrolling, searching, and all the messy behavior humans actually do. After that, three separate AI judges verified every session to make sure the actions matched the on-screen reality.
All of that added up to over a million individual actions used for training, giving the model extremely grounded behavior. The final result is an agent that doesn’t hallucinate clicks and doesn’t go rogue because it learned from full sequences of real web interactions. Most importantly, it runs locally, so latency drops and privacy shoots way up.
Performance-wise, the numbers are wild for a 7B model. On benchmarks like WebVoyager, WebtailBench, and DeepShop, FARA-7B matches or beats much larger agents while using a fraction of the tokens. A full task costs about two and a half cents compared to thirty cents for big GPT-powered agents. That’s a massive difference in both speed and affordability.
This is exactly what people hoped AI agents would eventually become—small, private, cheap, and accurate. FARA-7B is one of the first real signs that computer-use models are moving away from cloud-
After fourteen years of holding the second place spot, Apple is officially back on top as the number one smartphone maker. A lot of people online are giving credit to different parts of the lineup, but when I look at what people are actually using every day, a few things stand out. The bigger bodies and bigger batteries on the iPhone 17 Pro and Pro Max have made a real difference for creators, busy users, and anyone who pushes their phone hard. When you run VoiceOver or keep your screen brightness up, battery life matters, and these new phones finally delivered the stamina people were asking for.
Another detail that might not be talked about enough is the regular iPhone 17. From what we can see online and from what people are saying, the base model might be flying off shelves because it comes with more RAM and it is fully compatible with Apple Intelligence. That puts the regular model in a better position than last year’s base models and makes it more attractive for people who want AI features without jumping to the Pro models. It shows that Apple finally gave a little more love to the standard iPhone.
Now for my take. I currently use the iPhone 16, and even though I tested the 17 models, I am not in a rush to upgrade. One of the reasons is that I love the titanium build of the iPhone 16. When I hold the phone in my hand, especially comparing it to the iPhone 17, the titanium still feels solid, secure, and premium. Yes, the iPhone 17 is lighter, and aluminum helps with heat, but the titanium on the 16 just feels right to me when I am using it every day. It is one of those details that matters more in real life than on a spec sheet.
As for Apple being number one again, that is good news but not something that changes everything for the customer right away. It simply means more people are buying iPhones. The real benefit will come if Apple uses this momentum to keep improving the experience. If they want to stay competitive, especially with companies like Google baking Gemini deep into Android, Apple needs to push more in the direction of AI, better tools, and smarter integration across devices. Apple is great at what it does, but there is always room to improve the small things that matter daily.
OpenAI recently released two new open weight AI models, one at twenty billion parameters and another at one hundred twenty billion parameters. These models can run locally, without needing cloud servers, and that alone is a major shift in where AI is heading. Running locally means more privacy, more speed, and more control for everyday users. Instead of sending your data to some server far away, your device can process requests right where you are.
In my latest VoiceOver Pro video, I break down what open weight models really are and why they matter. Local AI can make devices faster, safer, and more reliable, especially for people who depend on assistive technology. This direction from OpenAI could bring stronger accessibility tools and reduce the need for constant internet access. It also puts pressure on big tech companies who rely on cloud AI, because the future might be leaning toward on device intelligence.
If you want a simple explanation of what these models can do and how they affect devices like the iPhone, iPad, and Mac, check out the full breakdown in the video below this post.
Apple’s new N1 networking chip is making a bigger impact than expected. Even though Apple describes the chip as functionally similar to the one inside the iPhone 16, real world speed tests show a clear jump in Wi Fi performance on the iPhone 17 models. According to Ookla’s data, the iPhone 17 family consistently delivered faster and more stable speeds when compared to the iPhone 16 across multiple regions, and even outperformed Android flagship phones during the same period.
The N1 networking chip inside the iPhone 17 integrates Wi Fi 7, Bluetooth 6, and Thread radios into a single custom Apple design. On paper, the specifications look almost identical to the Broadcom chip used in the iPhone 16. The N1 is still limited to 160 MHz channels and does not take advantage of Wi Fi 7’s faster 320 MHz channel support. But despite those limits, the real world results show the N1 delivering significantly higher performance for everyday users. Ookla’s Speedtest Intelligence data from the first six weeks after launch found that the median download and upload speeds on the iPhone 17 were up to forty percent higher than the iPhone 16. The biggest differences showed up in difficult Wi Fi conditions where the N1 chip provided up to sixty percent faster speeds compared to last year’s model.
Why This Matters
Many people judge upgrades based on what the spec sheet says, but this is a great example of why real world testing matters more. Even without full 320 MHz Wi Fi 7 support, the iPhone 17 is outperforming devices that technically have more bandwidth available. This includes top Android phones like the Pixel 10 and the Galaxy S25. In North America, where true Wi Fi 7 routers are becoming more available, the iPhone 17 still delivered the highest median and ninety percentile download speeds among major flagship phones. For regular users this means faster app downloads, smoother streaming, better video calls, and more reliable performance in busy Wi Fi environments.
My Take
Apple’s strength has always been in how their hardware and software work together. The N1 chip is another example of Apple optimizing for real world use rather than chasing specs on paper. Even in situations where the chip should be at a disadvantage, the iPhone 17 still performs at the top of the pack. As more people upgrade their routers and Wi Fi 7 becomes standard, the numbers may shift, but right now the consistency and stability of Apple’s custom chip are valuable improvements for anyone who depends on fast and reliable connectivity.
Apple’s ecosystem continues to impress me with how smoothly all the devices communicate with each other. When life gets busy, these small connections save time and reduce stress, especially when you misplace your iPhone. Instead of searching around the house, Apple gives you simple and accurate ways to locate it instantly.
If you have an Apple Watch, you can ping your phone in just a few seconds. Press the side button on the watch, scroll to the Ping Phone option, and activate it. If you are on the latest Apple Watch and iPhone, the watch will guide you directly to the phone. It will tell you how many feet away the phone is and whether to turn left or right. As you move in the correct direction, the watch gives you a quick buzz to confirm you are facing the right way. When you reach the phone, the iPhone will play a tone to let you know you have found it. It feels like both devices are helping you as a team.
This feature has saved me more times than I can count. There are moments when I walk into a room and the watch immediately gives me the direction and distance. The phone responds with a small ping, and within seconds I have it back in my hand. I go right back to what I was doing without losing focus or momentum.
You can also ping your phone using your voice. Just ask your assistant on the watch to ping your phone, and it will begin the same guided process. It shows the distance on the screen and gives direction until you reach your device. This accuracy is helpful for anyone, especially people who rely on feedback to move confidently through their space.
When all your Apple devices work together like this, it builds a system that supports your productivity. These features may seem simple, but once you use them in real situations, you start to understand how powerful the Apple ecosystem really is.
In my latest video I pull all of these stories together and break down what they could mean for us as everyday users. There are a few twists, and I keep the biggest surprises inside the video so you can hear them explained in real time.
The AI Bubble Is Coming
Artificial intelligence is growing faster than anything we have seen in technology for a long time. New models are launching every few months, companies are building massive data centers, and billions of dollars are being invested into training the next generation of AI. That growth sounds exciting, but it also raises serious questions when leaders like Sam Altman begin calling for government support to keep AI companies moving forward. When an industry starts asking for federal backup, it usually means the risks are bigger than most people realize.
In my new video I talk about why Sam Altman’s comments matter and how they connect to the larger pattern we are seeing across the AI industry. The companies building these systems are growing faster than any real regulations. We are watching a race for power, speed, and control with almost no limits in place. I also break down why the phrase “too big to fail” should make every taxpayer nervous. When companies become so large that they need government protection, we have to ask what is happening behind the scenes. Overspending, monopoly behavior, data collection, and privacy risks are all part of the conversation.
In the video I compare this moment to the early two thousands tech bubble. Back then, companies grew quickly, money poured in, and everyone believed the future was unstoppable. Then the bubble burst, and it shook the entire economy. With AI growing at this speed, it is fair to question if we are watching the same story play out again. When only a handful of companies control the intelligence that runs our apps, our devices, and even our decision making tools, the impact goes far beyond Silicon Valley.
If you care about technology, privacy, or the direction society is heading, this is a conversation worth paying attention to. AI has the power to help millions of people, but without guardrails and accountability, it can lead to the same mistakes we have already seen in tech history. I share my full thoughts in the video, and I would love to hear your opinion. The link is below this post.
Click here to watchThe AI Bubble Is Coming: Why Sam Altman Wants Government Backup
https://youtu.be/rrRn0VaqLrM
Perplexity AI has been gaining attention lately, and after testing it for myself I can see why. In my new VoiceOver Pro video, I explore whether this app could really be a smarter, faster alternative to Siri. Perplexity can take multiple requests at once and return clear results all in one response. For example, I asked for the weather in three different cities, and it came back with a full summary including wind speeds and temperatures for each location in seconds.
Beyond simple answers, I showed how Perplexity can interact with your apps. It can create calendar events, edit or customize them, and even delete them when plans change. It also connects with reminders so you can manage tasks hands-free. One of the most impressive parts was watching it compose and send an email. I gave it instructions, asked for edits, and it customized the message before sending it out to the contact I named. That’s something Siri still struggles to do consistently.
So that raises the big question: is Perplexity the next Siri? For now, Siri still has the advantage of being built into Apple’s ecosystem, but Perplexity shows what voice assistance could become. It’s fast, flexible, and feels like a glimpse of where Apple’s own AI might be headed.
You can watch the full walkthrough and see each test in action in my latest YouTube video. The link is below this post.
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