Рубрика: OpenAI

A few years ago, industry experts debated the role AI might play in various business sectors. Most of their comments were projections and theories. Not anymore. OpenAI has dramatically altered the business landscape, and its API is changing several products.

The sales demo world is no different. Walnut, a leading interactive sales demo platform, has announced the launch of a new product suite, ‘Ace’. The new product suite integrates with OpenAI’s tech, Gmail, Slack, and more to help sales professionals close more deals and gain insights into their workflows.

The launch comes at the right time for Walnut as sales teams worldwide are prioritizing efficiency and time management, in light of the economic downturn.

Walnut brings further innovation to the market

Walnut Ace leverages OpenAI to boost story script writing within its platform, saving sales teams an immense amount of time.

Practically speaking, OpenAI creates insightful scripts on top of demo guides, creates presenter notes, and even answers any prospect questions during self-guided demos via a responsive chat. This versatility goes a long way toward freeing a salesperson’s time to focus on deep customer issues that close a deal.

By eliminating tedious work like writing scripts, OpenAI’s tech removes even more barriers for salespeople looking to close more deals in their pipeline. Given OpenAI’s ability to generate text, it is a key ally in answering prospect questions and summarizing information too.

As a result, the very structure of a product demo meeting could change. Time will tell how these changes play out. However, the addition of OpenAI to Walnut’s product suite highlights the innovation the Tel Aviv-based company is bringing to the market.

OpenAI is changing products

On the surface, OpenAI’s tech looks like a chatbot that replies to user-generated prompts. However, its applications have made it nothing short of revolutionary for product design. Currently, its most well-known use lies in generating written content that does not need much creativity.

For instance, summaries of text or research-based information-round ups are some of its biggest use cases. An alternative use case is generating templated contracts that do not need much customization. For instance, a business that needs a liability waiver form can use OpenAI to create a document without spending thousands of dollars hiring a lawyer.

Crafting emails and integrating OpenAI into customer support roles are two further use cases. These are as simple as asking chatGPT to draft an email for a situation (“write an email explaining why I’ll be late for work to my manager”) and leveraging its API to answer simple customer questions.

While AI is currently present in a few chatbots, none of them are as smart as OpenAI. The algorithm can generate far more text based on the library of information it is provided compared to existing AI bots. The result is less burden on human customer support operators and more efficiency in these workflows.

Walnut’s use of OpenAI in answering prospect questions is an example of the algorithm’s chatbot-like usability. A salesperson can now theoretically send a prospect a demo link, remotely monitor usage, and help the prospect experience the product freely. Often, sales demos can feel like guided tours, with reps showcasing features that are bound to work.

However, with OpenAI’s assistance, reps can open the product to exploration, removing any lingering doubts in prospects’ minds and ensuring their questions are addressed throughout the journey.

AI integration is key in B2B SaaS

As AI’s abilities evolve, algorithms will increasingly play a critical role in B2B SaaS. From eliminating clerical or tedious tasks to predicting potential bottlenecks in processes, AI is set to revolutionize products across several niches.

Microsoft’s recent announcement of OpenAI’s integration with Bing search is a game-changer for SEO. A chatbot-like interface is set to summarize information instantly without the user having to click individual results. AI has been in gestation in other sectors that experience intricate workflows, such as the supply chain.

Whether designing delivery routes or predicting bottlenecks, AI is critical to product development in the supply chain. Predictive AI is still in the research phase. However, as the rapid rise of OpenAI proves, AI and ML algorithms can mature quickly and start assisting their human operators with several use cases.

AI is the key to innovation

As Walnut’s strategic move to incorporate OpenAI in its Ace product suite shows, leveraging AI is the key to delivering a great product experience. Without it, a product is likely going to feel analog and out of place.

Time will tell how AI develops, but for now, there is no doubt that AI is ready to transform several industries.

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OpenAI CEO Sam Altman claims ChatGPT is not a well-integrated product yet and is horrible

The CEO of OpenAI, Sam Altman, recently dubbed ChatGPT, the company’s artificial intelligence chatbot, a “terrible product” in a podcast interview. Altman spoke on ChatGPT’s general offering and present progress rather than its specific nature. Altman pointed up ChatGPT’s recurring error messages, too-straightforward design, and capacity difficulties as serious drawbacks.

Altman outlined the product’s significant shortcomings in a recent Hard Fork podcast by the New York Times. He stated: “A terrible product, ChatGPT. It wasn’t made to be utilized.” He said that the product has not yet been fully integrated.

When ChatGPT malfunctions, it frequently informs users that it is full or rejects their requests. He asserted that ChatGPT requires the user to go through a drawn-out process to complete tasks.

The recent integration of a fresh ChatGPT language model with Microsoft Bing was also discussed by Altman. He asserted that the inclusion of citations beneath a Bing search result will assist in addressing misleading information. Altman asserted that the new AI-powered Bing has greatly increased accuracy and usability compared to ChatGPT.

Greg Brockman, a second co-founder of OpenAI, has acknowledged that ChatGPT’s current iteration was only released as a last resort because of problems with beta testers internally.

ChatGPT has swiftly grown to have a sizable following despite its faults. It grew faster than Instagram and TikTok, reaching one million users a week after its introduction. Although ChatGPT’s technology is “interesting,” Altman recognized that it is still far from being a “fantastic, well-integrated solution.” But not all Bing users can get the newest version. They must first use their email IDs to sign up for a waiting list.

The ChatGPT bot, which debuted in November and has since gone viral, has upended the educational landscape and assisted students with their essays and tests. The bot can also write articles, lines of code, and cover letters for job applications. ChatGPT has received acclaim from Bill Gates, who claims it would “change our world”.

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GitHub’s OpenAI-powered developer tool with new capabilities goes live with enhanced Codex

The pair programming plugin for GitHub Copilot for Business, powered by OpenAI Codex, is now publicly available. It comes with an upgraded version of OpenAI Codex and a new real-time vulnerability filter that detects typical security flaws as you code in the editor.

Copilot for Business, an extension of the current Copilot for Individuals, was introduced by the Microsoft-owned code repository service in November. Each user of the program pays US$10 each month. Depending on the number of allocated Copilot seats, the monthly membership fee for Copilot for Business is US$19 per user.

Copilot’s code ideas are powered by OpenAI’s Codex, which converts natural language into code. With different editors, such as Microsoft Visual Studio, Neovim, VS Code, or JetBrains IDEs, Copilot may be utilized.

According to GitHub, Copilot now has an updated Codex model and additional features. Additionally, it has created a security vulnerability filter to enhance the security of Copilot’s code recommendations and aid developers in quickly identifying unsafe coding practices.

The new Codex model, which Microsoft is providing to developers through Azure OpenAI Services together with GPT-3.5 and DALL.E 2, should lead to a bigger proportion of code being authored by Copilot.

According to GitHub, when Copilot for people first debuted last year, on average, 27% of developers’ code files were produced by Copilot. Currently, the average for this statistic is 46% across all programming languages that are supported, while it is 61% for Java.

Although Copilot’s code acceptance rate is lower, it is still increasing. Developers typically accepted 27% of proposals in June 2022. In September, it increased to 30%, and by December, it had reached 35%.

Along with adopting a newer Codex model, Copilot also received the Fill-In-the-Center (FIM) “paradigm,” which improves upon the previous approach of simply considering the code prefix to account for known code suffixes and leaves a hole in the middle for Copilot to fill.

“This gives it additional background information about the code you want to write and how it should work with the rest of your program. We’ve created many techniques to offer FIM in GitHub Copilot’s code recommendations without any additional delay, and it regularly results in higher quality code suggestions “explains Shuyin Zhao, senior director of product management at GitHub.

A “lightweight client-side model” that learns about the user’s context has also been included in GitHub’s new VS Code addon to lessen the frequency of unwelcome recommendations. According to GitHub, there were 4.5% fewer unwelcome ideas as a consequence.

Large language models (LLMs) are also used by the new vulnerability filter to “approximate the behavior of static analysis tools.” Insecure coding patterns, such as hardcoded credentials, SQL injections, and path injections, are among the extremely prevalent security problems that GitHub claims it can identify in real-time and stop.

Microsoft could be able to increase the number of users who utilize GitHub by offering Copilot for people and corporations. According to a recent statistic, GitHub has 100 million members, which is far greater than most estimates of the world’s developer population. According to Thomas Dohmke, CEO of GitHub, the developers no longer work for software firms.

“They’re a growingly diverse and international community of people working across sectors, fiddling with code, design, and documents in their spare time, contributing to open source projects, doing scientific research, and more,” said Dohmke.

“They are individuals working on projects such as the PyTorch project, which drives AI and machine learning applications, as well as software for NASA, hospitals, and the movie industry. They also seek to support family members in communicating and recovering from the disease.”

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At least a dozen Google AI employees have just been stolen by OpenAI! Read more tech news

Good morning tech fam, here are some quick tech updates for you to catch on to!

What’s New Today: On ChatGPT Rival Bard, Google Provides Employees A List of “Do’s And Don’ts”.

Fast-Track Insights: XRP and ADA are Trashed by The CEO Of the Financial Data Business Estimize. Why?

According to the information, OpenAI has just hired at least 12 former Google AI employees. These engineers have been essential to the development of ChatGPT. In fact, OpenAI began the “poaching” activity very early for the benefit of ChatGPT. At least five Google employees were covertly hired by OpenAI in the weeks before ChatGPT went live in order to complete the necessary final touches and launch ChatGPT in November. A Google researcher who was in charge of creating machine learning models for the search engine was hired by OpenAI. Unknowingly, OpenAI has repurposed some of the early-stage AI technologies developed by Google into new revenue-generating services like chatbots and AI that create images and films out of text. The skills of Google have also. Google has slowly lost ground to such small start-ups in terms of talent.

Prabhakar Raghavan, Google’s vice president of search, issued an email to staff members asking for their assistance in ensuring that the company’s new ChatGPT competitor receives accurate responses. The email, which was first made public by CNBC, includes a link to a page with dos and don’ts and guidelines on how staff members should correct answers as they test Bard internally. Google offers suggestions for what staff members should think about “before teaching Bard” at the top of the “dos and don’ts” section. Some of the dos and don’ts mentioned in the email sent to Google workers are listed below. According to Google, comments should be “pleasant, easygoing and approachable,” written in the first person, and have an “unopinionated, neutral tone.” Dos and Don’ts Avoid forming assumptions based on racial, national, gender, age, religious, sexual, or ideological characteristics.

Trustworthy AI is an unachievable goal unless you understand what standards must be set. In an interview with Times of India, Arjan Durresi, a professor of computer science and a Purdue researcher based in Indianapolis, discussing the importance of instilling transparency and training AI to be trustworthy, said AI is in a transition phase. Many companies are eager to adopt AI will connect to his words. While on one hand, it has become a must-have technology, on the other hand trusting the outcomes has become a rather difficult proposition. Read More

Charlie Munger, a multibillionaire investor, is not a fan of cryptocurrencies. At the Daily Journal Corporation’s annual shareholder meeting on Wednesday, the vice chairman of Berkshire Hathaway referred to the virtual currency as “worthless.” He is a director of the publishing firm. “I sometimes refer to it as crypto “crappo,” and other times as “crypto s—-.” During a live broadcast of the event, Munger, 99, told CNBC’s Becky Quick that it was absurd that anyone would purchase this merchandise and added: “It’s totally utterly foolish idiotic gambling.” Cryptocurrency proponents contend that compared to conventional financial institutions, digital assets provide greater privacy, security, faster transaction times, and lower costs.

XRP and Cardano (ADA), two of the top ten cryptocurrencies, have come under fire from Leigh Drogen, CEO of financial data platform Estimize, who dubbed them “totally utterly useless.” In a recent tweet, Drogen described these two well-known cryptocurrencies as “totally utterly useless,” and he projected that in the ensuing market cycle, their market share would shift to assets that “really operate and matter.” Drogen stated that there were still $20 billion and $14 billion, respectively, of entirely pointless market capitalizations linked to XRP and ADA. The analyst continued, “In the next cycle, that’s going to flow to something that genuinely works and matters.”

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Real implications of ChatGPT for businesses in the current digital craze and the buzzword

OpenAI ChatGPT is a big language model that can create human-like texts in a conversational situation and do simple tasks. ChatGPT’s purpose is to develop a collaborative AI system capable of generating useful, interesting, and contextually appropriate text.

ChatGPT in Market Research: It is capacity to comprehend the context and give pertinent information might prove to be a helpful resource for gathering, analyzing, and comprehending market trends. Some of the tool’s key advantages include its ability to improve existing processes, collect qualitative information via conversational surveys, analyze data and extract features from large amounts of unstructured data, provide valued market intelligence, and save researchers significant time and effort.

Uses of ChatGPT in Market Research:

Chatbot Surveys

GPT may be used to create conversational and intelligent surveys to collect consumer feedback and insights. In comparison to traditional surveys, this enables more genuine and engaging data collecting.

Customer Segmentation

Based on the replies, ChatGPT may be used to categorize consumer data.

Trend Analysis

ChatGPT may be used to uncover trends in consumer attitudes and behavior by analyzing massive quantities of feedback from customers, social media posts, and other unorganized data sources.

Sentiment Analysis

ChatGPT may be used to analyze customer feedback and identify a brand’s, product’s, or service’s overall sentiment, delivering significant insights into the market study and relationship building.

Text Classifications

ChatGPT may be used to categorize customer comments and other unstructured data based on certain themes such as features of the product, customer service, and marketing initiatives, hence increasing the analysis and knowledge of client wants and preferences.

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