0.8 C
Washington

The True Cost Of AI Training Data | Shaip

The Cost of Bad DataBad data can cost your company team morale, your competitive edge, and other tangible consequences that go unnoticed. We define bad data as any dataset that is unclean, raw, irrelevant, outdated, inaccurate, or full of spelling errors. Bad data can spoil your AI model by introducing bias and corrupting your algorithms with skewed results. Inadequate data can result in extending your time to market by 2X as you have to restart collecting and annotating relevant data for your AI training phase.Additionally, you are likely to bring down the confidence and morale of your AI development team as they are consistently being exposed to poor and inaccurate results. Technically, you will encounter multiple feedback loops, forcing you to revisit your model for optimization and corrective measures.Management ExpensesThe costliest expense when training your AI is management-related. All costs involving the administration of your organization or enterprise, tangibles, and intangibles constitute management expenses. When all administration expenses are tabulated, you realize there are other more straightforward ways to get your AI training data sourced with minimal effort and costs.The SolutionThe expenses we’ve outlined above can easily be eliminated through what we call ‘paid data collection and annotation services.’Or simply, outsourcing.

When you outsource, you employ a specialized team to work on data sourcing, compilation, and annotation, ensuring you receive AI-ready data. You will be in the best position possible, ready to feed impeccable data into your AI system.Hire AI data vendor only requires you to pay for the service that is provided. There’s no need to spend time hiring a team, overworking to meet deadlines, experiencing the consequences of bad data, or dealing with low team esteem and morale-driven conflicts. Outsourcing makes space for the time you need to focus on optimizing your product, working on promotional strategies, pitching to investors, and other crucial tasks.Why Shaip?At Shaip, we have expert data scientists and annotators who have access to diverse resources. Regardless of your market segment, niche, or requirements, you will find the quality data you need to train your AI model. Working with us is a rewarding experience because of our transparent modus operandi; we also adhere to stringent deadlines and focus on healthy collaboration practices.If you are looking to reduce unnecessary expenses and get your AI system operating at cost, reach out to us today.

━ more like this

Newbury BS cuts resi, expat, landlord rates by up to 30bps  – Mortgage Strategy

Newbury Building Society has cut fixed-rate offers by up to 30 basis points across a range of mortgage products including standard residential, shared...

Rate and Term Refinances Are Up a Whopping 300% from a Year Ago

What a difference a year makes.While the mortgage industry has been purchase loan-heavy for several years now, it could finally be starting to shift.A...

Goldman Sachs loses profit after hits from GreenSky, real estate

Second-quarter profit fell 58% to $1.22 billion, or $3.08 a share, due to steep declines in trading and investment banking and losses related to...

Building Data Science Pipelines Using Pandas

Image generated with ChatGPT   Pandas is one of the most popular data manipulation and analysis tools available, known for its ease of use and powerful...

#240 – Neal Stephenson: Sci-Fi, Space, Aliens, AI, VR & the Future of Humanity

Podcast: Play in new window | DownloadSubscribe: Spotify | TuneIn | Neal Stephenson is a sci-fi writer (Snow Crash, Cryptonomicon, and new book Termination...