Ocean Protocol

AUGUST 23, 2023

Back then, there were no calculators, pencils, or chat GPT— imagine how people got around or knew what coffee to order?! The earliest libraries were typically housed in temples and contained religious texts, but over time, libraries began to expand their collections to include works on various subjects.

Big Data 52

Big Data Big Data Algorithm Machine Learning 52

Dataconomy

OCTOBER 18, 2023

Grab a cup of coffee An example of the Meta Quest 3 passthrough mode comes from TikTok user Carrot Survivor. The user builds a physical bridge between the virtual and real worlds by holding the video he watches without taking off his Meta Quest and taking it to the balcony of his house with his coffee.

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ML @ CMU

APRIL 14, 2023

The robot should not need to wait until a human instructs the robot to “pick the remote control off the floor and place it on the coffee table”. The neural makes use of a graph made from training houses, which we call the memex graph. Neural graph module for determining where to place an object.

Artificial Intelligence 363

Artificial Intelligence Artificial Intelligence Machine Learning Machine Learning 363

AWS Machine Learning Blog

FEBRUARY 19, 2024

Mask prompt – A mask prompt is a natural language text description of the elements you want to affect, that uses an in-house text-to-segmentation model. Coffee maker - A 12-cup programmable coffee maker in brushed steel with removable water tank and keep warm plate. - For more information, refer to Prompt Engineering Guidelines.

AWS 99

AWS Python AI AI 99

Data Science Dojo

JANUARY 8, 2024

The core of MoE: Meet the experts: Imagine a bustling marketplace where each stall houses a master in their craft. Buckle up, fellow AI enthusiasts, and prepare to witness the power of specialization in the world of intelligent machines! Source: Deepgram 1.

Natural Language Processing 243

Natural Language Processing AI AI Artificial Intelligence 243

Snorkel AI

JUNE 15, 2023

We’re then making a number of expert decisions with our in-house team. We have our own in-house sentiment model where we’re predicting whether things are positive, negative, or neutral about a particular entity. Then, we are able to use techniques and solve important problems like knowledge graph completeness and other things.

AI 52

AI AI Data Scientist Machine Learning 52

Snorkel AI

JUNE 15, 2023

We’re then making a number of expert decisions with our in-house team. We have our own in-house sentiment model where we’re predicting whether things are positive, negative, or neutral about a particular entity. Then, we are able to use techniques and solve important problems like knowledge graph completeness and other things.

AI 52

AI AI Data Scientist Machine Learning 52

Ocean Protocol

SEPTEMBER 12, 2023

Imagine accountable prediction feeds for not only for rain, but also wind, sea temperature, road congestion, train delays, ETH prices, NVID prices, housing prices, and more. Would you rather a farmer in Costa Rica selling a sack of coffee beans for $5, or Starbucks selling 5 beans’ worth of coffee for $5? It’s the same for data.

ML 59

ML ML AI AI 59

Hacker News

JULY 2, 2023

Housing all members of the design team in one small office made communicating easier. It resembled a house more than an office, having a communal area much like a living room, with smaller rooms off to the side for more privacy in working or talking.

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AWS Machine Learning Blog

JUNE 14, 2023

occupation ech-support, Craft-repair, Other-service, Sales, Exec-managerial, Prof-specialty, Handlers-cleaners, Machine-op-inspct, Adm-clerical, Farming-fishing, Transport-moving, Priv-house-serv, Protective-serv, Armed-Forces relationship Wife, Own-child, Husband, Not-in-family, Other-relative, Unmarried.

AWS 77

AWS ML ML Data Scientist 77

The MLOps Blog

MARCH 21, 2023

Can the tool integrate with open standard, open source, and more importantly, the existing in-house stack (including testing and monitoring ecosystems)? Only a handful of companies are heavily investing in building in-house ML platforms. The first iteration was built on an in-house PySpark solution.

Machine Learning 69

Machine Learning Machine Learning Data Scientist ML 69