Man-made Intelligence (AI) can not just have its specialized lead on the market but can also help to improve one’s life. Most it needs can be described as proper course in to conquer research problems and its considering in a specific way.
AI arguements for homelessness and HIV through the naive process. Initially, people talked with 4-5 homeless because their peers, nonetheless it wasn’t feasible because of the schooling cost. Taking AI in the picture for capturing which nodes influence the most leading to effect maximization difficulty, I strongly believe AJE has the potential to reduce effects which could support us decrease homelessness. Bryan talked about the influence maximization algorithm which will faces challenges due to poor records of no . of homeless which might require several weeks of work to execute in-person interviews. Bryan mentioned how these AI techniques could then simply lead to community structure and friendship paradox. While community paradox offers difficulty in a particular environment even though the friendship paradox works by surveying a unique node after which surveying its neighbor to have a better response to influencing nodes. I think this might save our time and initiatives and help all of us to put more effort in the areas where were actually having the results, inside our case choosing the peer leaders.
I think there can be an alternative to this solution by combining technology with non-tech and believe government along with the educational start could offer a helping hand to the desolate people. Having proper overall health education reaches most important with this stage to avoid the spread of HIV. Instead of having peer commanders go to them, we could possess weekend seminars for them within their locality and invite them over, acquire their info and apply a machine learning formula to solve the situation in that area.
Moreover, collecting the family info from the metropolis department we can establish a rules to protect every single family from homelessness by simply creating anti-homelessness service. The info collected could be passed through different machine learning algorithms which includes random forest, neural sites, boosted trees, and logistic regression. This will eventually help us to investigate that the households which are likely to face homelessness are also applying to anti-homelessness support. This would better define the goals of eradicating homelessness and HIV. The goal of this kind of idea is to not only help the homeless but also to stop homelessness.
I think Bryan did an admirable job explaining this current condition and various algorithms to take on those circumstances. The ideas were evidently articulated using algorithmic formula and graphs though I believe it could have got better if he had regarded other instances as well, rather than removing homelessness, prevention can be equally important and necessary. His thoughts had been well received by the market, implementing these kinds of a great social problem using AI and Machine learning is a huge process. I really love his operate. Also, it might have helped him to demonstrate well in the event he had shown an interview with homeless persons, it could have got helped the group to actually imagine the whole condition. Overall it had been a great idea and i also hope to notice it as a big success.