New ask Hacker News story: Ask HN: How many % of Machine Learning projects “fail”?
Ask HN: How many % of Machine Learning projects “fail”?
2 by satishgupta | 0 comments on Hacker News.
There are all these reports/surveys claiming ~80% of ML projects fail: - Jan 2019: https://ift.tt/3iDERtC Gartner predicted that through 2020, 80% of AI projects will remain alchemy, run by wizards and through 2022, only 20% of analytic insights will deliver business outcomes. - May 2019: https://ift.tt/3p8hgUb Dimensional Research - Alegion Survey reported 78% of AI or ML projects stall at some stage before deployment, and 81% admit the process of training AI with data is more difficult than they expected. - July 2019: https://ift.tt/2LWNVLL VentureBeat reported 87% of data science projects never make it into production. There used to be similar claims in 1990s about failure of Software Development projects: - 1994: https://ift.tt/39c40Zj The Standish Group’s CHAOS Report in 1994 claimed that only 16% of the software projects succeeded. That claim was doubted: https://ift.tt/2KE4bmD Overtime, CHAOS reports became nuanced: https://ift.tt/2TUe7JV My questions are: - How "failure" is defined for ML projects, when to call a project failure? - Is failure rate really 80%?
2 by satishgupta | 0 comments on Hacker News.
There are all these reports/surveys claiming ~80% of ML projects fail: - Jan 2019: https://ift.tt/3iDERtC Gartner predicted that through 2020, 80% of AI projects will remain alchemy, run by wizards and through 2022, only 20% of analytic insights will deliver business outcomes. - May 2019: https://ift.tt/3p8hgUb Dimensional Research - Alegion Survey reported 78% of AI or ML projects stall at some stage before deployment, and 81% admit the process of training AI with data is more difficult than they expected. - July 2019: https://ift.tt/2LWNVLL VentureBeat reported 87% of data science projects never make it into production. There used to be similar claims in 1990s about failure of Software Development projects: - 1994: https://ift.tt/39c40Zj The Standish Group’s CHAOS Report in 1994 claimed that only 16% of the software projects succeeded. That claim was doubted: https://ift.tt/2KE4bmD Overtime, CHAOS reports became nuanced: https://ift.tt/2TUe7JV My questions are: - How "failure" is defined for ML projects, when to call a project failure? - Is failure rate really 80%?
