If you want to start building generative AI applications from scratch, you\u2019re going to need to overcome some major hurdles, like:<\/p>\n
<\/p>\n
- \n
- The Skills Barrier<\/strong>: It can take roughly 4 years to cultivate the expertise needed to become a proficient deep learning engineer. Out of the numerous deep learning experts in the field, only 5,000 people have the prowess to build and train LLMs from the ground up. (1<\/a>)<\/li>\n<\/ul>\n
<\/p>\n
\n
\ud83e\udd2f Training GPT-3 solely on an NVIDIA Tesla V100 GPU could take a whopping 288 years!<\/strong><\/p>\n<\/blockquote>\n
<\/p>\n
- \n
- The Technical Constraints<\/strong>: As an example, training GPT-3 solely on an NVIDIA Tesla V100 GPU could take a whopping 288 years (2<\/a>). Though spreading the computation over multiple GPUs can speed this up, the financial cost becomes a significant barrier.<\/li>\n<\/ul>\n
<\/p>\n
- \n
- The Economic Implications<\/strong>\u00a0(3<\/a>): To put it in perspective, training Meta’s Llama 2 with 7b and 70b parameters, respectively, required vast GPU hours. In monetary terms, the training cost is around:\n
- \n
- ~10b parameters: Approximately $150,000<\/li>\n
- ~100b parameters: Around $1,500,000.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n
<\/p>\n
In short, to build a generative AI application from scratch, it’s not just the 4 years of learning you\u2019ll need to do, but there\u2019s also the significant time and financial investments you\u2019ll need.<\/p>\n
<\/p>\n
Looking For A Simpler Route?<\/h1>\n
\n\n<\/div>\n<\/div>\n<\/div>\nHowever, there’s an easier path forward. Foundation models, such as those by OpenAI, Cohere, and PaLM, provide APIs that even someone with moderate Python skills can start building with.<\/p>\n
These models come pre-trained, eliminating the enormous costs and expertise previously mentioned. It’s practically a plug-and-play method for generative AI development.<\/p>\n
<\/p>\n
The Most Direct Path Of Them All: No Code AI Tools!<\/h2>\n
\n\n<\/div>\n<\/div>\n<\/div>\nIf you’re seeking an even more streamlined approach, enter the world of no code AI tools!<\/p>\n
<\/p>\n
Why No-Code?<\/h3>\n
\n\n<\/div>\n<\/div>\n<\/div>\nNo-code platforms are revolutionizing the landscape. Even without in-depth coding or deep learning knowledge, these platforms provide an easy-to-use interface to build generative AI applications.<\/p>\n
With respect to generative AI, no code AI tools are all about making advanced AI technologies accessible and practical for everyone.<\/p>\n
\n\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n\u23f0 Don’t Miss This Free Training: Building a NoCode AWS Bedrock LLM App on Flowise<\/h3>\n
\n\n<\/div>\n<\/div>\n<\/div>\n\ud83d\udd39\u00a0This show-stopping new training<\/a>\u00a0is your golden ticket to step into the future of No-Code generative AI app development.<\/p>\n
<\/p>\n
\n\n \n<\/picture> ![\"get](\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\")
<\/a><\/p>\n** This no code AI tool training was delivered live and is now available here on-demand<\/a> **<\/p>\n<\/div>\n<\/figure>\n<\/div>\n
\ud83c\udf10 Register Now!<\/a><\/p>\n
<\/p>\n
Topic<\/strong>:\u00a0How to Build a NoCode AWS Bedrock LLM App on Flowise<\/a><\/p>\n
Date \/ Time<\/strong>: On-Demand Replay<\/p>\n
Location<\/strong>:\u00a0Sign-up here<\/a><\/p>\n
<\/p>\n
Give us just 60 short minutes and you\u2019ll witness and learn the intricacies of building NoCode AWS Bedrock LLM Apps on Flowise.<\/p>\n
<\/p>\n
What you\u2019ll get when you attend:<\/h3>\n
- \n
- Witness cutting-edge no-code AI tools & integrations<\/strong>: Discover how the marriage between AWS Bedrock, Flowise AI, and SingleStoreDB is laying the groundwork for future of dynamic LLM applications.<\/li>\n<\/ul>\n
- \n
- Get hands-on training<\/strong>: Michael Connor, the eminent head of AWS Consumer Package Goods, will be delivering a demo that was live-recorded. Experience for yourself the magic of building LLM apps without any coding requirements! \u2013 all streamlined on SingleStoreDB.<\/li>\n<\/ul>\n
- \n
- Grow your data expertise<\/strong>: See the power of vector databases, learn the capabilities of AWS Bedrock, and get acquainted with Flowise AI’s intuitive drag & drop tool. Elevate your skills and stay ahead in the AI landscape.<\/li>\n<\/ul>\n
<\/h3>\n
<\/p>\n
Times \u2018a ticking! \u23f0<\/h3>\n
\n\n<\/div>\n<\/div>\n<\/div>\nThe clock is ticking before we take this free training<\/a> down (or put it behind a paywall!). This is your chance to witness the next big thing in AI app development. Ensure you’re at the forefront of this technological revolution.<\/p>\n
\ud83c\udf10 Register Now!<\/a><\/p>\n
Don’t let this opportunity slip through your fingers. Get on board, learn from the experts, and embrace the future, today.<\/p>\n
<\/p>\n
Enjoy!<\/p>\n
<\/p>\nLillian Pierson, PE<\/p>\n
Shop<\/a>\u00a0|\u00a0Blog<\/a>\u00a0|\u00a0LinkedIn<\/a><\/p>\n
PS.<\/strong> Don’t miss this other free training we did showing how to build a voice cloning app using OpenAI<\/a>.<\/p>\n
Disclaimer: This blog post may include sponsored content or affiliate links and I may possibly earn a small commission if you purchase something after clicking the link. Thank you for supporting small business \u2665\ufe0f.<\/em><\/p>\n
- Grow your data expertise<\/strong>: See the power of vector databases, learn the capabilities of AWS Bedrock, and get acquainted with Flowise AI’s intuitive drag & drop tool. Elevate your skills and stay ahead in the AI landscape.<\/li>\n<\/ul>\n
- Get hands-on training<\/strong>: Michael Connor, the eminent head of AWS Consumer Package Goods, will be delivering a demo that was live-recorded. Experience for yourself the magic of building LLM apps without any coding requirements! \u2013 all streamlined on SingleStoreDB.<\/li>\n<\/ul>\n
- Witness cutting-edge no-code AI tools & integrations<\/strong>: Discover how the marriage between AWS Bedrock, Flowise AI, and SingleStoreDB is laying the groundwork for future of dynamic LLM applications.<\/li>\n<\/ul>\n
- The Economic Implications<\/strong>\u00a0(3<\/a>): To put it in perspective, training Meta’s Llama 2 with 7b and 70b parameters, respectively, required vast GPU hours. In monetary terms, the training cost is around:\n
- The Technical Constraints<\/strong>: As an example, training GPT-3 solely on an NVIDIA Tesla V100 GPU could take a whopping 288 years (2<\/a>). Though spreading the computation over multiple GPUs can speed this up, the financial cost becomes a significant barrier.<\/li>\n<\/ul>\n
![\"get](\"https:\/\/substackcdn.com\/image\/fetch\/w_424,c_limit,f_webp,q_auto:good,fl_progressive:steep\/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F4023f3f3-9810-49af-b02d-dc5f2c11fcde_1600x900.png)
<\/a><\/p>\n![\"\"](\"https:\/\/www.data-mania.com\/blog\/wp-content\/uploads\/2023\/10\/Lillian-Pierson-2023-Headshot-150x150.jpg\")
<\/p>\n