Seems useful, but only half useful given that most structured interviews are more based on the role the candidate is applying for than the candidates resume.
So it might be good idea to ask for the user to upload the job posting/description as well, that way your GenAi engine can adapt the structured interview questions to what the target company typically asks for that kind of role.
Also instead of email it might be good to give a linkedin link option as well? That way you can:
1) Make life easier for the candidate as you can get the CV data out of his/her profile
2) Get richer data that can help you offer other kind of
career services in the future
3) Track which user that used your service actually landed a job that you trained him for
"The NTP monograph concluded that higher levels of fluoride exposure, such as drinking water containing more than 1.5 milligrams of fluoride per liter, are associated with lower IQ in children.
The NTP review was designed to evaluate total fluoride exposure from all sources and was not designed to evaluate the health effects of fluoridated drinking water alone.
It is important to note, however, that there were insufficient data to determine if the low fluoride level of 0.7 mg/L currently recommended for U.S. community water supplies has a negative effect on children’s IQ."
Now seriously, by Llama being "sort of" open source, it does not seem to be something someone can fork and develop/evolve it without Meta, right? If one day Meta comes and says "we are closing Llama and evolving it in a proprietary mode from now on" would this Llama indie scene continue to exist?
If this is the case wouldn't this be considered a dumping strategy by Meta, to cut revenue streams from other platforms (Gemini/OpenAI/Anthropic) and contain their growth?
"good enough" is incredibly subjective here. Maybe good enough for you, but there are many things that are not possible with either the dataset or the weights being available.
And some things are impossible even with both the dataset and weights. Say you wanted to train the same model as is released, using Meta's hypothetically released training data. You also need to know the starting parameters, the specific hardware and it's quirks during training, the order the data is trained in as well as any other preprocessing techniques used to treat the text.
Considering how ludicrously expensive it would be to even attempt a ground-up retrain (as well as how it might be impossible), weights are enough for 99% of people.
Good-enough? Please please type out what a truely open source ai model with open weights and open data would be like. I picture it like a Tower of Babel! Very far from "Good-enough"!
Realistically the problem here might just be that the concept of open source doesn't really fit machine learning models very well, and we should stop trying to force it.
Sharing the end product, but not the tools and resources used to produce it, is how open source has always worked. If I develop software for a commercial operating system using a commercial toolchain, and distribute the source code under GPL, we would call that software open source. Others who get the code don't automatically get the ability to develop it themselves, but that's kind of beside the point. I don't have the rights to publicly redistribute those tools, anyway; the only part I can put under an open source license is the part for which I have copyright.
Training data for a LLM like Llama works similarly when it comes to copyright law. They don't own copyright and/or redistribution rights for all of it, so they can't make it open, even if they want to.
If that seems unsatisfying, that's because it is. Unfortunately, though, I don't think the Free Software community is going to get very far by continuing to try to fight today's openness and digital sovereignty battles using tactics and doctrine that were developed in the 20th century.
It does fit it. Perfectly. It's incredible. Like an Internet of all Human Knowledge released before 1965. OpenAI could of done this. The battle to me is just people respecting ideas instead of saying they are impossible or unnecessary because what we have is good enough.
Location would be my bet. Not sure if IKEA has the same source for their products (might have change sources because of taxes, logistic costs, local incentives etc...); and as a commenter specified in this thread, different regions have different conditions (climate, cleaning culture, etc) that might also impact the durability of the products.
I haven't tested the app but the main service is pretty near natural language.
If 11labs app get to the main service quality and start accepting ePubs, it will be the death of Audible.
> If 11labs app get to the main service quality and start accepting ePubs, it will be the death of Audible.
The app from this announcement does accept epubs. Just tested a couple and had no issues. Haven't used 11labs before, but the quality was good and didn't have any major issues with an English voice even with some spot checked fantasy names/terms or chemical names.
I believe Audible is already using non human speakers as well and just making up names for the narrators. I can tell since sometimes pronunciations are wrong and sound similar to TTS mistakes.
Ah - I have probably listened to maybe 8-10 audiobooks and all ones that have been recommended to me as excellent. I guess I just assumed that that’s what audiobooks are like, which I guess doesn’t make sense.
My main reason of returning or not listening to audiobooks, be it with Audible or competitors, has been either a) a whiny or nasal voice, or, b) a strong accent that i dislike (e.g. strong British or Australian accent).
I have found myself finding more new books by checking which other books a specific narrator has voiced, rather than finding a book I want to listen to and hoping for a good narrator.
That's not an easter egg, that feature probably increased the number of likes in videos since it made the button easier to spot when users were looking for it (which is when it is mentioned on videos).
So that sweet engagement KPI is positively impacted and Youtube's CRO/experiment/Ab testing team gets their cookies.
There are probably various small tweaks like this in the UI.
This is the same way all airlines in the world work since the invention of Revenue/Yield Management. Which is basically price discrimination to get the biggest piece of the value.
Airlines will mostly segment client based on things like Minimum Stay (in destination) and how many days before the flight the ticket was bought to find the most desired of all users: The business traveler.
SSO is (roughly) the same thing, companies who would like SSO are probably the ones in the corporate level, and this is an efficient way to find them. Of course there are false positives, but software companies are willing to live with those to get the biggest part of the pie.
And this is actually good for users, as it allows for the other users who have more flexibility to pay a lot less (both at airlines and software) than they would pay if those companies didn't discriminate.
This is a catch 22, because Bolsonaro team was using social media and fake news to move dumb masses towards their objective, pretty similar to Trump in the US.
The judge in question, with his despotic tendencies, was in an open war against Bolsonaro (started by Bolsonaro) and stretched the powers of the judiciary to bring Bolsonaro down.
Now, we have 2 wrongs here. But how one should react to all of this?
So it might be good idea to ask for the user to upload the job posting/description as well, that way your GenAi engine can adapt the structured interview questions to what the target company typically asks for that kind of role.
Also instead of email it might be good to give a linkedin link option as well? That way you can:
1) Make life easier for the candidate as you can get the CV data out of his/her profile
2) Get richer data that can help you offer other kind of career services in the future
3) Track which user that used your service actually landed a job that you trained him for