Definitely a large need gap. Solution comes to personalised news at micro level.
Several years back we attempted a customised news platform - https://talkabout.co.in which could address your grievances at some places, but a real solution for this need gap is not just a customisable news platform but a highly personalised one.
It would very interesting to crack this need gap without access to large personal data, it all relies upon the initial on-boarding questionnaire regarding the user's qualifications, current job description and coming up with career trajectories using generalised data. Current state of machine learning algorithms can definitely help create a plausible solution.
UPDATE: Android is now supporting hearing aid pairing with Android - https://www.youtube.com/watch?v=P5ZmqEoOheQ&t=0s , this doesn't relate to the need gap directly i.e. enabling hearing aid features via SW processing for TWS earphones.
Another common way these smartphone accessories sellers fake their reviews & rating in these ecommerce sites is by having accessories for different smartphones in the same listing, so when the buyer comes to the product page they would see the reviews for the case, tempered glass of another smartphone which may/may not be true for the smartphone they are buying it for.
There few websites which claim to check for fake reviews in the ecommerce sites such as https://www.fakespot.com/ , https://reviewmeta.com/ but I didn't find them accurate enough in my tests to recommend.
Perhaps there is a need gap for a service to detect fake reviews and rating by using language scores(NLP), checking past reviews of the users and correlating with the seller's score. The review system for anything on the Internet, say Playstore or Ecommerce by default is dependent upon the 'law of large numbers' i.e the fake reviews get sidelined and true reviews/ratings come up when several real customers start to rate it.
But unfortunately in a country like India, the law of large numbers can be applied effectively to create fake reviews as well due its large population. Perhaps there is a need gap for a better review system as a whole.
Definitely a large need gap. Solution comes to personalised news at micro level.
Several years back we attempted a customised news platform - https://talkabout.co.in which could address your grievances at some places, but a real solution for this need gap is not just a customisable news platform but a highly personalised one.
It would very interesting to crack this need gap without access to large personal data, it all relies upon the initial on-boarding questionnaire regarding the user's qualifications, current job description and coming up with career trajectories using generalised data. Current state of machine learning algorithms can definitely help create a plausible solution.
UPDATE: Android is now supporting hearing aid pairing with Android - https://www.youtube.com/watch?v=P5ZmqEoOheQ&t=0s , this doesn't relate to the need gap directly i.e. enabling hearing aid features via SW processing for TWS earphones.
Another common way these smartphone accessories sellers fake their reviews & rating in these ecommerce sites is by having accessories for different smartphones in the same listing, so when the buyer comes to the product page they would see the reviews for the case, tempered glass of another smartphone which may/may not be true for the smartphone they are buying it for.
There few websites which claim to check for fake reviews in the ecommerce sites such as https://www.fakespot.com/ , https://reviewmeta.com/ but I didn't find them accurate enough in my tests to recommend.
Perhaps there is a need gap for a service to detect fake reviews and rating by using language scores(NLP), checking past reviews of the users and correlating with the seller's score. The review system for anything on the Internet, say Playstore or Ecommerce by default is dependent upon the 'law of large numbers' i.e the fake reviews get sidelined and true reviews/ratings come up when several real customers start to rate it.
But unfortunately in a country like India, the law of large numbers can be applied effectively to create fake reviews as well due its large population. Perhaps there is a need gap for a better review system as a whole.