Loading video...

Video Failed to Load

Go Home

🚨MUST READ UPDATE: Baltimore Bridge Collapse The Cargo Ships BLACK BOX Reveals the VDR Sensor Data “Ceased” Recording for 2 Minutes Prior to Impact 🔴 NTSB investigator Marcel Muise held a press conference to reveal the data on the DALI’s black box, also known as the Voyage Data Recorder...

6,416,305 views • 2 years ago •via X (Twitter)

8 Comments

Steve Ferguson's profile picture
Steve Ferguson2 years ago

Those pesky "coincidences" are stacking up

Rob Michaels's profile picture
Rob Michaels2 years ago

We better not question anything or we’ll be evil conspiracy theorists. This story will be buried right next to Vegas and the Maui land grab going on.

Snow Miser's profile picture
Snow Miser2 years ago

And still, hardly and chatter about the thermite charges that cut the bridge into sections, making this a controlled demolition. The boat accident is just for cover.

TiredOfTyranny061's profile picture
TiredOfTyranny0612 years ago

Why on earth would they just drop the port anchor? That would be why the ship turned sharply left and ran into the bridge. That seems deliberate to me. They were going to clear it, then should have dropped both port and starboard anchors at once to slow down the vessel to a stop?

Don Eanes's profile picture
Don Eanes2 years ago

Big surprise, you look at the original video, you see it turn toward the support structure, and you see thick diesel smoke pouring out the stack, (like they gunned it).

America First AF 🇺🇸's profile picture
America First AF 🇺🇸2 years ago

doesn't that huge plume of smoke mean they hit the gas hard af?

Jin Saotome's Dangerous Toys's profile picture
Jin Saotome's Dangerous Toys2 years ago

The ship was hacked and you can watch as the crew tries to reset the system twice by shutting off the main power, but to no avail. You can even watch the black diesel smoke as the engines accelerate towards the bridge pylon. It was planned and everyone in the government is lying

Tang trader's profile picture
Tang trader2 years ago

10 billion for bridge 10 billion for Ukraine.hopefully this explains it.

Related Videos

We just launched a major new Data Engineering Professional Certificate on Coursera! Data underlies all modern AI systems, and engineers who know how to build systems to store and serve it are in high demand. If you're interested in learning this skill, please check out this 4-course sequence, which is designed to make you job-ready to be a Data Engineer. This is a new specialization taught by Joe Reis, the co-author of the best-selling book “Fundamentals of Data Engineering," in collaboration with AWS. (Disclosure, I serve on Amazon's board.) For many AI systems, data engineering is 80% of the work, and modeling is 20%. But people’s attention on these two topics is often flipped. This makes the job of the data engineer particularly important. In this professional certificate, you'll learn foundational data engineering skills while implementing modern data architectures using open-source tools: - Learn the key steps of the data lifecycle, to generate, ingest, store, transform, and serve data. - Learn to align with organizational goals to design the data pipeline right for your business' needs. - Understand how to make necessary trade-offs between speed, scalability, security, and cost. Joe has distilled into this specialization decades of experience helping startups and large companies with data infrastructure. He is also joined by 17 other industry leaders in the data field, who will help you learn in-demand skills for the growing field of data engineering. Please sign up here:

Andrew Ng

118,937 views • 1 year ago

Major program launch: Data Analytics Professional Certificate! This large, five-course sequence takes you all the way to being job-ready as a data analyst, and shows how to use Generative AI as a thought partner to enhance your work in this role. Offered by on Coursera, this is taught by Sean Barnes, Ph.D., a Data Science & Engineering Leader at Netflix. Analyzing data remains one of the most important skills in where the world is going with AI. This comprehensive certificate takes you all the way to being job-ready. Each course comes with practical projects demonstrated in real-world contexts, such as analyzing sales data for a Korean bakery, video game sales trends across different regions, or identifying factors impacting customer retention for a communications company. You'll also work on estimating fire distribution for forest fire prevention, analyzing how a diamond's properties affect its market value, and developing predictive models for retail sales analysis, carbon emissions, and coral reef conservation. Here's some of what you'll learn: - How to define data and categorize it into its many types such as discrete & continuous numerical, structured & unstructured, time series, categorical, and know what insights can be derived from the different types of data categories. - How to differentiate between data-related job roles and their responsibilities, and how data flows through an organization from the moment of capture to decision-making. - How to perform data processing functions and apply conditional formatting in spreadsheets to extract business value from your data using statistical calculations and best practices for visualizing and interpreting data. - How to use LLMs for stakeholder analysis, data exploration, and data visualization. - Best practices for using LLMs for as a thought partner to data analysis work By the end of this professional certificate program, you will have learned core statistical concepts, analysis techniques, and visualization methodologies that will serve as the foundation for working as a data analyst. The world needs more data analysts, especially ones who know how to use modern generative AI. With data science roles projected to grow 36% by 2033, the skills taught in this program create new professional opportunities in data. Sign up here!

Andrew Ng

85,012 views • 1 year ago

David Friedberg: Michael Burry’s Datacenter Math is Wrong “I actually think Michael Burberry's got this wrong.” “What Michael Burry is saying is that all of these hyperscalers have extended their depreciation schedule or the useful life of their data centers by roughly 2x, which cuts the operating costs in half when they report it in earnings. And so it's making their earnings inflate.” “So he's claiming they're cooking the books. Google first made this change in Q1 of 2021, where they said the servers are now going from 3 to 4 years. Separately in 2021, Google took networking equipment from 3 to 5 years. And then in 2023, they took it from 5 to 6 years.” “And so this is a result of this effort where they went in and did an analysis. So what happened?” “What happened in the data centers is that the data centers transitioned from being primarily data storage and data transfer systems, where you would use hard drives and RAM and memory to store data and then transmit it back out, to being data processing centers because of the AI boom.” “So as AI became more important in the data center, more of the dollars that are going into data centers were allocated towards chips from data storage, which initially was hard drives.” “And then suddenly, when you put these processors in to process the data to do AI, the majority of the spend and the majority of the energy is going towards the processors.” “I made some calls and I checked around with some other friends, and everyone says the same thing: that these 7-8 year old TPUs and GPUs that are sitting in the data centers are still being used and they're being used at 100% utilization.” “So that actually justifies and validates the depreciation schedule being much longer versus shorter.”

The All-In Podcast

304,297 views • 8 months ago

Yesterday, Ian Whiffin confirmed what Richard Green/the #KarenRead defense said in Trial 1, thus confirming that John O’Keefe arrived at 34 Fairview 3 minutes & 1 second before the Commonwealth’s GPS/location data points show: “[The monotonic clock] is not a clock that can be trusted to see when events occur.” Only the display time is accurate when determining when something actually happened. “All activity is related to that (the display) clock.” “You have to take the values that the monotonic clock provides and add or subtract different values, which are essentially offsets, to get the correct time.” That’s a major problem for the Commonwealth — because Whiffin’s entire Waze location analysis is built on the MONOTONIC TIMESTAMPS! And somehow, neither Whiffin nor Hank Brennan seems to grasp what just happened: They accidentally proved the defense’s theory! Specifically, because the Waze app runs on monotonic time programming and not the display time programming, the timestamps associated with the cached locations from Waze on John’s iPhone are 3 minutes and 1 second fast/ahead, or have a 181 second offset (see attached evidence exhibit from trial 1 with the specific conversions). This means that John O’Keefe arrived at 34 Fairview at approximately 12:21:37am, give or take, and not at 12:24:38am as the Commonwealth asserts, as Waze is based off of the monotonic timestamps, not the display clock timestamps. Consequently, this means John arrives at 34 Fairview BEFORE his Apple Health data recorded him taking flights of stairs, which didn’t first occur until 12:22:14am, therefore meaning that approximately 40 seconds after arriving at the house, John O’Keefe first began climbing some stairs. It suddenly becomes a lot harder for the Commonwealth to discredit the reliability of Apple Health data confirming John went inside the house when his location data also put him there. Why would the Commonwealth rely on the wrong timestamps when conducting their 15+ months after the fact GPS/location data analysis? Because it was right after the defense had first made public John O’Keefe’s Apple Health data showing flights of stairs climbed upon John’s arrival at 34 Fairview—thus establishing that he did in fact go inside the house. They needed to keep John out of the house to have any case, so they opted for discrediting the Apple Health data they so regularly rely upon in their criminal prosecutions, while deliberately only looking at John’s phone location data sourced from the one app that uses monotonic time programming without converting those timestamps to the display time (or subtracting the 3 mins. 1 second offset). By exploiting the incorrect monotonic timestamps of the cached Waze location data, the Commonwealth was able to claim that John’s phone location data showed he’d not yet arrived at 34 Fairview by the time his Apple Health data showed him climbing flights of stairs inside the house. To convert any of John O’Keefe’s Waze data that Whiffin presented into real time, you need to subtract 3 full minutes from each monotonic timestamp. So when Whiffin bizarrely testified that John was climbing stairs while driving down Oakdale at 12:22 AM? Yeah — that actually happened at 12:19 AM. And when he claimed Karen pulled up to 34 Fairview at 12:24 AM? That was really at 12:21 AM. Both times perfectly aligned with the Defense’s timeline. Not the Commonwealth’s. And Hank Brennan? Well, he’s got his expert, Ian Whiffin, casually confirming that John O’Keefe was walking into 34 Fairview at 12:21 AM, and climbing stairs at 12:22 AM. At this point, you really have to ask: Are the Commonwealth’s witnesses planning to leave anything for the Defense to rebut? Or are they just going to blow up their own case — one by one? Because this? This is getting insane. #IanWhiffin #Cellebrite #NorfolkCounty #KarenReadTrial #KarenReadTrial2 #FreeKarenRead #JusticeForJohnOKeefe

Olivia

179,619 views • 1 year ago