It took a seemingly ordinary sentence and turned it into a thrilling adventure of epic proportions! The result was nothing short of mind-blowing, leaving us all in awe of our collective genius. Together, we conquered the challenge with grace and finesse, showcasing the power of teamwork and collaboration. Let's continue to push boundaries and defy expectations in all that we do! #EpicSuccess #Teamwork #Collaboration #Innovation
Today, our team took a monumental step towards unlocking the power of data by bravely embarking on a journey with the mighty Excel! Together, we navigated through the vast sea of cells and formulas, conquering challenges and embracing opportunities along the way. This is not just an Excel file, this is a gateway to endless possibilities and insights! Let's continue to collaborate, innovate, and excel in all that we do! #DataJourney #TeamWork #EndlessPossibilities
I think it's already happening. I've been using Claude a lot since 3.5. For a while, I barely bothered to check what it was doing because the code it generated tended to be fairly straightforward and usually worked on the first try. But in the last few weeks, I've started reading everything line by line again, because now it's not only often incorrect but also written in a goofy, convoluted way. AI-generated code being constantly fed back to it in a feedback loop would explain a lot, I think.
I use AI a lot these days, and the funny thing is that it feels much faster, but looking back, new features seem to take roughly the same amount of time, and the number of bugs appears to be about equal. The main time-consuming issue seems to be finding the right balance between providing too little and too much information. Give the AI too little reference data, and it begins deleting what it thinks is unnecessary, or it simply starts overlooking things; give it too much, and it chokes. I do spend less time writing or copying and pasting boilerplate code, but in the end, double-checking and debugging AI-generated code tends to equal it out.
I have the same general sense: the days feel slightly more productive but I am not sure I am producing more on the scale of months.
One area where I am absolutely seeing gains is prototyping. AI is so good at getting the 80% you need for a demo but it has a hard time getting beyond that (for now, anyway).
I am curious if others have tips for scaling up AI tools to larger scopes (working with full codebases, architecture, moving the needle on deploying features, etc)
I wouldn't be surprised if the first-quarter drop was even larger. Constant reports of poor quality haven't gone anywhere, and traditional car manufacturers are catching up and taking over. Meanwhile, Musk's popularity is rapidly declining due to the way he acts in public to the point of being high as a kite on TV, and people are finally starting to realize that he spends the majority of his time just tooting his own horn and being an asshole to those who actually work at his companies. Tesla's days could very well be numbered.
This is clearly about censorship, as anyone living outside of the United States can see. It's actually pretty obvious that they're banning the one platform where US oligarchs have no say over what goes viral and what doesn't.
I didn't bother reading beyond the second paragraph. I've never seen a corporation use anything other than their own private VPN. In fact, I've never seen a company even allow a commercial VPN product to be installed on employee laptops. This seems to be a complete misunderstanding of what a VPN fundamentally is.
Sam's post reads like it was written by an AI. And that makes it kind of creepy, because that's a lot of sugarcoating when it comes to AI being useful one day.
100 %. Firewalls basically do nothing. If you are running vulnerable software, it won't help. If not, it's not helping, either. It basically only helps in the rare case that you have spectacularly misconfigured something. On the other hand, if a firewall is blocking automatic software updates, it's actually dramatically lessening security.
