Models & Labs · United States

How Oracle turns days of work into minutes with ChatGPT and Codex

Credited to OpenAI · openai.com · 15h ago

Across recruiting, engineering, and operations, Oracle turns specialist knowledge into fast, repeatable workflows with ChatGPT Work and Codex.

Decrease in the time it takes for talent acquisition research

Over a hundred thousand employees across Oracle are using ChatGPT Work and Codex, from talent acquisition to Oracle Applications Lab to the IT organization. In each case, work that used to rely on specialists and take days can now be done by anyone and is complete in minutes. Recruiters skip days of market research, business users describe an outcome instead of hunting for a report, and technical leads build tools that used to take a full team months.

“We’ve built our talent market intelligence tool using ChatGPT Work, and it’s really revolutionized how we do the front end of our recruitment process.”

Making recruiting research more efficient

The talent acquisition team used ChatGPT Work to build a talent market intelligence tool that takes a job description, researches comparable roles, benchmarks compensation, and assesses the talent pool across relevant locations. The tool arms the recruiter with valuable information that they need going into a conversation with the hiring manager, information that previously took 2–4 days to compile.

“We’ve gone from zero to a hundred,” says Jan Ackerman, Senior Vice President and Global Head of Talent Acquisition at Oracle. “Now we’re able to sit down and prep for about 15 to 20 minutes using the tool that we’ve built using [ChatGPT] Work.”

Not only is the process faster, but it’s also more consistent. Recruiters used to run the intake process differently from one search to the next, but with the talent market intelligence tool, the process is consistent, so every hiring manager has the same quality of data and insights, no matter which recruiter they worked with.

Business users get the answers they need faster

The Oracle Applications Lab team, which helps run many of Oracle’s core business processes, built an ontology of the company’s objects, relationships, and rules, so a plain-language business question can be turned into a reliable SQL query with Codex. A business user describes the outcome they want, and Codex decides which internal systems to call, gathers the information, and returns an analysis, a report, or an application.

That’s a change from how work used to get done. Lam said one user came to him after asking a question that would normally have taken her a couple of hours to answer. She told Lam, “With the new tool, I put in the request and got a response almost immediately.” When she checked the result against the old manual process, the numbers matched exactly.

In production engineering, site reliability engineers use Codex to gather relevant context about an incident and automatically pull up the right playbook. SREs spend more time guiding decisions and less time hunting for information. “A typical simple incident that used to take an hour to resolve can now be handled in minutes,” says Lam.

Even as Codex takes on more of the work, Lam is careful to note that none of this runs on autopilot. Someone still has to make sure the underlying system is built right.

“Business users now describe the outcome they want instead of hunting for a report. That is a major shift. I would even call it a business transformation.”

Leadership lessons

While AI builds the tools, the people are still responsible for the output. A few lessons stand out:

Give the correct guardrails. “You have to still be very responsible about your system design, your architecture, your security, and how you would like Codex to structure the code for you,” says Lam.

Provide prototypes instead of specs. “Normally, I put [my idea] down on paper, but now I put it down in a prototype,” says Barry Shilmover, Vice President and Technical Advisor to the CIO.

Own the code. “If you don’t work alongside Codex, you’re going to get into a situation of having lots of code that is not going to be maintainable,” says Lam.

The Oracle team is completely shifting how the company operates with AI. Across recruiting, analytics, and engineering, each line of business described an outcome and let Codex and ChatGPT handle how the work gets done. With thousands of ChatGPT and Codex users already, Oracle employees use AI across countless work tasks. As Shilmover puts it, “I don’t know what the answer is because I don’t know what my next problem to solve will be. I just know that one of the first things I’ll do is I’ll leverage Codex to do that.”

Join the new era of work

Keep reading

Models & LabsUnited States

OpenAI Asia-Pacific Policy Head to Leave After Six Months in Job

Credited to Bloomberg$ · bloomberg.com4h ago

Useful

OpenAI’s most senior Asia-Pacific public policy executive is departing after six months in the job, according to a person familiar with the matter, just as the ChatGPT maker faces scrutiny from regulators in the region.

View the article · $Bloomberg

Front Method

Models & Labs · United States

Anthropic launches critical infrastructure program and free OSS Scanner for open source

Credited to SiliconANGLE · siliconangle.com · 8h ago

Photograph · SiliconANGLE

Anthropic PBC today launched a program that brings its frontier models and onsite engineers to the security companies protecting power grids, water systems and other critical infrastructure.

OSS Scanner, launched with it, offers open-source projects free periodic vulnerability scans from the company’s strongest models. Both fall under a new effort Anthropic calls the Anthropic Cyber Mission.

The Critical Infrastructure Defense Program starts with the outside providers that operators of every size already rely on for advice on which fixes are safe to apply to a running system. Eleven of those providers signed on as founding partners.

Accenture plc, Booz Allen Hamilton Inc., Deloitte & Touche LLP and PricewaterhouseCoopers LLP come from the consulting side, where they run security programs for operators. Security vendors make up the biggest bloc, with industrial specialists Dragos Inc., Insane Cyber Inc. and Nozomi Networks Inc. joining CrowdStrike Holdings Inc. and Palo Alto Networks Inc. Hitachi Ltd. and Rockwell Automation Inc. build and patch the hardware itself.

The program is aimed at operational technology in plants, substations and water systems, where equipment built to run for decades often cannot be taken offline for a patch. Known flaws can sit there for years. Anthropic said several partners are already using Claude to fix vulnerabilities and to help their customers do the same. More partners and sectors are due to join over the coming months.

Andrew Turner, president of commercial cyber at Booz Allen, called operational technology “the next frontier for autonomous AI-enabled attacks” in comments published with the announcement. What matters now, he said, is how much control artificial intelligence can gain over an industrial process and how fast.

The announcement leaves out the commercial terms. Axios noted in its coverage that Anthropic has not said whether partners get free model access or who covers the computing costs. The same report questioned how partners will test and deploy fixes without disrupting utility operations.

The open-source half of today’s news grew out of a backlog in Anthropic’s own disclosure work. Of the more than 29,000 candidate vulnerabilities its models turned up in widely used software over the past six months, staff have manually reviewed about 6,000. A growing number of maintainers who received early reports asked for the whole unreviewed batch, proposed patches included, and nearly 5,000 such reports have gone out so far.

OSS Scanner turns that arrangement into a standing service for other eligible projects. Google LLC’s OSS-Fuzz, which runs fuzzers against open-source code, inspired the setup.

Every report includes a self-contained reproducer. Early tester Anton Arapov of the OpenSSL Corporation said a report with a real exploit attached is “basically job done for an engineer.” Where the model can manage it, a candidate patch comes with the write-up, and a bisection of the code history shows when the flaw was introduced.

Reports from the new service go straight to maintainers without human review so they arrive faster. Some will contain mistakes as a result, such as a wrong severity rating, Anthropic said.

To gauge how often that happens, Anthropic tested the scanner’s accuracy before opening it to more projects. The expert penetration testers who vet the company’s coordinated disclosures checked 97 critical and high-severity findings from an early version across 48 projects and cleared 85 for disclosure.

Of the other 12, all but one were real bugs that duplicated known issues or other findings from the scan. Embedded encryption library developer wolfSSL Inc. said all but two of the 74 reports it received during early trials were valid and that five became CVEs.

Core maintainers can enroll by submitting a pull request to an Anthropic GitHub repository. Eligibility follows the OSS-Fuzz test of “critical impact on infrastructure and user security,” with decisions made case by case. Projects without the staff to keep up with raw findings will still get human-verified reports through Anthropic’s existing disclosure process.

The Defender Advantage Fund that Anthropic set up in August pays to keep the scanner free. The company has also put money into the Python Software Foundation and the Apache Software Foundation, as well as Alpha-Omega and OpenSSF through the Linux Foundation.

Both launches draw on lessons from Project Glasswing. That program gave vetted organizations access to Claude Mythos from April until it was folded into an expanded Cyber Verification Program earlier this week. Finding vulnerabilities has never been easier, according to Anthropic. Verifying, prioritizing and fixing them remains hard, and the company said Glasswing has not yet cut cyber risk by enough.

Anthropic expects AI to favor defenders within two years. For now the cost of exploiting a flaw keeps falling, and verifying and repairing one is still slow work that depends on people. With operational technology, a fix may have to wait until it can go safely onto running machinery, and in rare cases that could take decades.

Support our mission to keep content open and free by engaging with theCUBE community. Join theCUBE’s Alumni Trust Network, where technology leaders connect, share intelligence and create opportunities.

Are you an AWS customer? Support SiliconANGLE financially by buying your AWS services from our Marketplace portal page and links: https://siliconangle.com/aws-marketplace/

Founded by tech visionaries John Furrier and Dave Vellante, SiliconANGLE Media has built a dynamic ecosystem of industry-leading digital media brands that reach 15+ million elite tech professionals. Our new proprietary theCUBE AI Video Cloud is breaking ground in audience interaction, leveraging theCUBEai.com neural network to help technology companies make data-driven decisions and stay at the forefront of industry conversations.

Alphabet spinoff Isomorphic Labs reportedly raising funding at up to $50B valuation

CoreWeave Forge aims to speed up the AI improvement loop

AI agent developer Manus raises $500M+ at reported $4B valuation

CoreWeave makes the case for an open, full-stack AI cloud

Automation Anywhere acquires Boost.ai to expand customer-facing voice AI

Liquid AI builds personal AI around device-level context

Join our community